Mercurial > forge
changeset 11827:9fd86811bb0d octave-forge
econometrics: moved to a separate mercurial repo
author | carandraug |
---|---|
date | Mon, 17 Jun 2013 21:08:20 +0000 |
parents | 823b01ff4f5e |
children | 2555b363673c |
files | main/econometrics/COPYING main/econometrics/DESCRIPTION main/econometrics/INDEX main/econometrics/NEWS main/econometrics/doc/README main/econometrics/inst/delta_method.m main/econometrics/inst/gmm_estimate.m main/econometrics/inst/gmm_example.m main/econometrics/inst/gmm_obj.m main/econometrics/inst/gmm_results.m main/econometrics/inst/gmm_variance.m main/econometrics/inst/gmm_variance_inefficient.m main/econometrics/inst/kernel_density.m main/econometrics/inst/kernel_density_cvscore.m main/econometrics/inst/kernel_example.m main/econometrics/inst/kernel_optimal_bandwidth.m main/econometrics/inst/kernel_regression.m main/econometrics/inst/kernel_regression_cvscore.m main/econometrics/inst/mle_estimate.m main/econometrics/inst/mle_example.m main/econometrics/inst/mle_obj.m main/econometrics/inst/mle_obj_nodes.m main/econometrics/inst/mle_results.m main/econometrics/inst/nls_estimate.m main/econometrics/inst/nls_example.m main/econometrics/inst/nls_obj.m main/econometrics/inst/parameterize.m main/econometrics/inst/poisson.m main/econometrics/inst/poisson_moments.m main/econometrics/inst/prettyprint.m main/econometrics/inst/prettyprint_c.m main/econometrics/inst/private/average_moments.m main/econometrics/inst/private/kernel_density_nodes.m main/econometrics/inst/private/kernel_epanechnikov.m main/econometrics/inst/private/kernel_normal.m main/econometrics/inst/private/kernel_regression_nodes.m main/econometrics/inst/private/mle_variance.m main/econometrics/inst/private/nls_obj_nodes.m main/econometrics/inst/private/sum_moments_nodes.m main/econometrics/inst/scale_data.m main/econometrics/inst/unscale_parameters.m main/econometrics/src/Makefile main/econometrics/src/__kernel_weights.cc |
diffstat | 43 files changed, 0 insertions(+), 2731 deletions(-) [+] |
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--- a/main/econometrics/COPYING Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,674 +0,0 @@ - GNU GENERAL PUBLIC LICENSE - Version 3, 29 June 2007 - - Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/> - Everyone is permitted to copy and distribute verbatim copies - of this license document, but changing it is not allowed. - - Preamble - - The GNU General Public License is a free, copyleft license for -software and other kinds of works. - - The licenses for most software and other practical works are designed -to take away your freedom to share and change the works. By contrast, -the GNU General Public License is intended to guarantee your freedom to -share and change all versions of a program--to make sure it remains free -software for all its users. We, the Free Software Foundation, use the -GNU General Public License for most of our software; it applies also to -any other work released this way by its authors. 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If not, see <http://www.gnu.org/licenses/>. - -Also add information on how to contact you by electronic and paper mail. - - If the program does terminal interaction, make it output a short -notice like this when it starts in an interactive mode: - - <program> Copyright (C) <year> <name of author> - This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. - This is free software, and you are welcome to redistribute it - under certain conditions; type `show c' for details. - -The hypothetical commands `show w' and `show c' should show the appropriate -parts of the General Public License. Of course, your program's commands -might be different; for a GUI interface, you would use an "about box". - - You should also get your employer (if you work as a programmer) or school, -if any, to sign a "copyright disclaimer" for the program, if necessary. -For more information on this, and how to apply and follow the GNU GPL, see -<http://www.gnu.org/licenses/>. - - The GNU General Public License does not permit incorporating your program -into proprietary programs. If your program is a subroutine library, you -may consider it more useful to permit linking proprietary applications with -the library. If this is what you want to do, use the GNU Lesser General -Public License instead of this License. But first, please read -<http://www.gnu.org/philosophy/why-not-lgpl.html>.
--- a/main/econometrics/DESCRIPTION Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,11 +0,0 @@ -Name: Econometrics -Version: 1.1.1 -Date: 2013-02-17 -Author: Michael Creel <michael.creel@uab.es> -Maintainer: Nir Krakauer <nkrakauer@ccny.cuny.edu> -Title: Econometrics. -Description: Econometrics functions including MLE and GMM based techniques. -Depends: octave (>= 2.9.7), optim -Autoload: no -License: GPLv3+ -Url: http://octave.sf.net
--- a/main/econometrics/INDEX Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,18 +0,0 @@ -econometrics >> Econometrics -Econometrics - delta_method - gmm_estimate gmm_example gmm_obj gmm_results gmm_variance gmm_variance_inefficient - mle_estimate mle_example mle_obj mle_results - parameterize prettyprint scale_data unscale_parameters - nls_estimate nls_obj - mle_obj_nodes - nls_example - poisson - poisson_moments - prettyprint_c - kernel_density - kernel_density_cvscore - kernel_example - kernel_optimal_bandwidth - kernel_regression - kernel_regression_cvscore
--- a/main/econometrics/NEWS Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,16 +0,0 @@ -Summary of important user-visible changes for econometrics 1.1.1: -------------------------------------------------------------------- - - ** Fixed a bug that affected gmm_example by making gmm_obj no longer private - -Summary of important user-visible changes for econometrics 1.1.0: -------------------------------------------------------------------- - - ** The following functions have been made private: - - average_moments gmm_obj kernel_density_nodes - __kernel_epanechnikov __kernel_normal kernel_regression_nodes - mle_variance nls_obj_nodes sum_moments_nodes - - ** Calls to deprecated functions have been replaced for compatibility - with newer octave versions.
--- a/main/econometrics/doc/README Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,14 +0,0 @@ -The main functions for end users are: - -mle_estimate.m Performs estimation by MLE -mle_results.m Performs estimatiion by MLE and shows results -mle_example.m Example - - -gmm_estimate.m Performs estimation by GMM -gmm_results.m Performs estimatiion by GMM and shows results -gmm_example.m Example - - -The other functions are mostly for internal use, or for use by -advanced users.
--- a/main/econometrics/inst/delta_method.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,24 +0,0 @@ -## Copyright (C) 2003, 2004 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## Computes Delta method mean and covariance of a nonlinear -## transformation defined by "func" - -function [theta_transf, var_transf] = delta_method(func, theta, otherargs, vartheta) - theta_transf = feval(func, theta, otherargs); - D = numgradient(func, {theta, otherargs}); - var_transf = D * vartheta * D'; - -endfunction
--- a/main/econometrics/inst/gmm_estimate.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,74 +0,0 @@ -## Copyright (C) 2003, 2004, 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## usage: [theta, obj_value, convergence, iters] = -## gmm_estimate(theta, data, weight, moments, momentargs, control, nslaves) -## -## inputs: -## theta: column vector initial parameters -## data: data matrix -## weight: the GMM weight matrix -## moments: name of function computes the moments -## (should return nXg matrix of contributions) -## momentargs: (cell) additional inputs needed to compute moments. -## May be empty ("") -## control: (optional) BFGS or SA controls (see bfgsmin and samin). -## May be empty (""). -## nslaves: (optional) number of slaves if executed in parallel -## (requires MPITB) -## -## outputs: -## theta: GMM estimate of parameters -## obj_value: the value of the gmm obj. function -## convergence: return code from bfgsmin -## (1 means success, see bfgsmin for details) -## iters: number of BFGS iteration used -## -## please type "gmm_example" while in octave to see an example - -## call the minimizing routine -function [theta, obj_value, convergence, iters] = gmm_estimate(theta, data, weight, moments, momentargs, control, nslaves) - - if nargin < 5 error("gmm_estimate: 5 arguments required"); endif - if nargin < 6 control = {-1}; endif # default controls - if !iscell(control) control = {-1}; endif # default controls if receive placeholder - if nargin < 7 nslaves = 0; endif - - if nslaves > 0 - global NSLAVES PARALLEL NEWORLD NSLAVES TAG; - LAM_Init(nslaves); - # Send the data to all nodes - NumCmds_Send({"data", "weight", "moments", "momentargs"}, {data, weight, moments, momentargs}); - endif - - # bfgs or sa? - if (size(control,1)*size(control,2) == 0) # use default bfgs if no control - control = {Inf,0,1,1}; - method = "bfgs"; - elseif (size(control,1)*size(control,2) < 11) - method = "bfgs"; - else method = "sa"; - endif - - - if strcmp(method, "bfgs") - [theta, obj_value, convergence, iters] = bfgsmin("gmm_obj", {theta, data, weight, moments, momentargs}, control); - elseif strcmp(method, "sa") - [theta, obj_value, convergence] = samin("gmm_obj", {theta, data, weight, moments, momentargs}, control); - endif - - if nslaves > 0 LAM_Finalize; endif # clean up - -endfunction
--- a/main/econometrics/inst/gmm_example.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,63 +0,0 @@ -## Copyright (C) 2003, 2004, 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## GMM example file, shows initial consistent estimator, -## estimation of efficient weight, and second round -## efficient estimator - -n = 1000; -k = 5; - -x = [ones(n,1) randn(n,k-1)]; -w = [x, rand(n,1)]; -theta_true = ones(k,1); -lambda = exp(x*theta_true); -y = poissrnd(lambda); -[xs, scalecoef] = scale_data(x); - -# The arguments for gmm_estimate -theta = zeros(k,1); -data = [y xs w]; -weight = eye(columns(w)); -moments = "poisson_moments"; -momentargs = {k}; # needed to know where x ends and w starts - -# additional args for gmm_results -names = char("theta1", "theta2", "theta3", "theta4", "theta5"); -gmmtitle = "Poisson GMM trial"; -control = {100,0,1,1}; - - -# initial consistent estimate: only used to get efficient weight matrix, no screen output -[theta, obj_value, convergence] = gmm_estimate(theta, data, weight, moments, momentargs, control); - -# efficient weight matrix -# this method is valid when moments are not autocorrelated -# the user is reponsible to properly estimate the efficient weight -m = feval(moments, theta, data, momentargs); -weight = inverse(cov(m)); - -# second round efficient estimator -gmm_results(theta, data, weight, moments, momentargs, names, gmmtitle, scalecoef, control); -printf("\nThe true parameter values used to generate the data:\n"); -prettyprint(theta_true, names, "value"); - -# Example doing estimation in parallel on a cluster (requires MPITB) -# uncomment the following if you have MPITB installed -# nslaves = 1; -# theta = zeros(k,1); -# nslaves = 1; -# title = "GMM estimation done in parallel"; -# gmm_results(theta, data, weight, moments, momentargs, names, gmmtitle, scalecoef, control, nslaves);
--- a/main/econometrics/inst/gmm_obj.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,31 +0,0 @@ -## Copyright (C) 2003, 2004, 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## The GMM objective function, for internal use by gmm_estimate -## This is scaled so that it converges to a finite number. -## To get the chi-square specification -## test you need to multiply by n (the sample size) - -function obj_value = gmm_obj(theta, data, weight, moments, momentargs) - - m = average_moments(theta, data, moments, momentargs); - - obj_value = m' * weight *m; - - if (((abs(obj_value) == Inf)) || (isnan(obj_value))) - obj_value = realmax; - endif - -endfunction
--- a/main/econometrics/inst/gmm_results.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,104 +0,0 @@ -## Copyright (C) 2003, 2004, 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## usage: [theta, V, obj_value] = -## gmm_results(theta, data, weight, moments, momentargs, names, title, unscale, control, nslaves) -## -## inputs: -## theta: column vector initial parameters -## data: data matrix -## weight: the GMM weight matrix -## moments: name of function computes the moments -## (should return nXg matrix of contributions) -## momentargs: (cell) additional inputs needed to compute moments. -## May be empty ("") -## names: vector of parameter names -## e.g., names = char("param1", "param2"); -## title: string, describes model estimated -## unscale: (optional) cell that holds means and std. dev. of data -## (see scale_data) -## control: (optional) BFGS or SA controls (see bfgsmin and samin). May be empty (""). -## nslaves: (optional) number of slaves if executed in parallel -## (requires MPITB) -## -## outputs: -## theta: GMM estimated parameters -## V: estimate of covariance of parameters. Assumes the weight matrix -## is optimal (inverse of covariance of moments) -## obj_value: the value of the GMM objective function -## -## please type "gmm_example" while in octave to see an example - -function [theta, V, obj_value] = gmm_results(theta, data, weight, moments, momentargs, names, title, unscale, control, nslaves) - - if nargin < 10 nslaves = 0; endif # serial by default - - if nargin < 9 - [theta, obj_value, convergence] = gmm_estimate(theta, data, weight, moments, momentargs, "", nslaves); - else - [theta, obj_value, convergence] = gmm_estimate(theta, data, weight, moments, momentargs, control, nslaves); - endif - - - m = feval(moments, theta, data, momentargs); # find out how many obsns. we have - n = rows(m); - - if convergence == 1 - convergence="Normal convergence"; - else - convergence="No convergence"; - endif - - V = gmm_variance(theta, data, weight, moments, momentargs); - - # unscale results if argument has been passed - # this puts coefficients into scale corresponding to the original data - if nargin > 7 - if iscell(unscale) - [theta, V] = unscale_parameters(theta, V, unscale); - endif - endif - - [theta, V] = delta_method("parameterize", theta, {data, moments, momentargs}, V); - - k = rows(theta); - se = sqrt(diag(V)); - - printf("\n\n******************************************************\n"); - disp(title); - printf("\nGMM Estimation Results\n"); - printf("BFGS convergence: %s\n", convergence); - printf("\nObjective function value: %f\n", obj_value); - printf("Observations: %d\n", n); - - junk = "X^2 test"; - df = n - k; - if df > 0 - clabels = char("Value","df","p-value"); - a = [n*obj_value, df, 1 - chi2cdf(n*obj_value, df)]; - printf("\n"); - prettyprint(a, junk, clabels); - else - disp("\nExactly identified, no spec. test"); - end; - - # results for parameters - a =[theta, se, theta./se, 2 - 2*normcdf(abs(theta ./ se))]; - clabels = char("estimate", "st. err", "t-stat", "p-value"); - printf("\n"); - prettyprint(a, names, clabels); - - printf("******************************************************\n"); -endfunction
--- a/main/econometrics/inst/gmm_variance.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,24 +0,0 @@ -## Copyright (C) 2003, 2004 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## GMM variance, which assumes weights are optimal - -function V = gmm_variance(theta, data, weight, moments, momentargs) - D = numgradient("average_moments", {theta, data, moments, momentargs}); - D = D'; - m = feval(moments, theta, data, momentargs); # find out how many obsns. we have - n = rows(m); - V = (1/n)*inv(D*weight*D'); -endfunction
--- a/main/econometrics/inst/gmm_variance_inefficient.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,28 +0,0 @@ -## Copyright (C) 2003, 2004 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## GMM variance, which assumes weights are not optimal - -function V = gmm_variance_inefficient(theta, data, weight, omega, moments, momentargs) - D = numgradient("average_moments", {theta, data, moments, momentargs}); - D = D'; - - n = rows(data); - - J = D*weight*D'; - J = inv(J); - I = D*weight*omega*weight*D'; - V = (1/n)*J*I*J; -endfunction
--- a/main/econometrics/inst/kernel_density.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,119 +0,0 @@ -## Copyright (C) 2006 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## kernel_density: multivariate kernel density estimator -## -## usage: -## dens = kernel_density(eval_points, data, bandwidth) -## -## inputs: -## eval_points: PxK matrix of points at which to calculate the density -## data: NxK matrix of data points -## bandwidth: positive scalar, the smoothing parameter. The fit -## is more smooth as the bandwidth increases. -## kernel (optional): string. Name of the kernel function. Default is -## Gaussian kernel. -## prewhiten bool (optional): default false. If true, rotate data -## using Choleski decomposition of inverse of covariance, -## to approximate independence after the transformation, which -## makes a product kernel a reasonable choice. -## do_cv: bool (optional). default false. If true, calculate leave-1-out -## density for cross validation -## computenodes: int (optional, default 0). -## Number of compute nodes for parallel evaluation -## debug: bool (optional, default false). show results on compute nodes if doing -## a parallel run -## outputs: -## dens: Px1 vector: the fitted density value at each of the P evaluation points. -## -## References: -## Wand, M.P. and Jones, M.C. (1995), 'Kernel smoothing'. -## http://www.xplore-stat.de/ebooks/scripts/spm/html/spmhtmlframe73.html - -function z = kernel_density(eval_points, data, bandwidth, kernel, prewhiten, do_cv, computenodes, debug) - - if nargin < 2; error("kernel_density: at least 2 arguments are required"); endif - - n = rows(data); - k = columns(data); - - - # set defaults for optional args - if (nargin < 3) bandwidth = (n ^ (-1/(4+k))); endif # bandwidth - see Li and Racine pg. 26 - if (nargin < 4) kernel = "kernel_normal"; endif # what kernel? - if (nargin < 5) prewhiten = false; endif # automatic prewhitening? - if (nargin < 6) do_cv = false; endif # ordinary or leave-1-out - if (nargin < 7) computenodes = 0; endif # parallel? - if (nargin < 8) debug = false; endif; # debug? - - nn = rows(eval_points); - n = rows(data); - if prewhiten - H = bandwidth*chol(cov(data)); - else - H = bandwidth; - endif - - # Inverse bandwidth matrix H_inv - H_inv = inv(H); - - # weight by inverse bandwidth matrix - eval_points = eval_points*H_inv; - data = data*H_inv; - - # check if doing this parallel or serial - global PARALLEL NSLAVES NEWORLD NSLAVES TAG - PARALLEL = 0; - - if computenodes > 0 - PARALLEL = 1; - NSLAVES = computenodes; - LAM_Init(computenodes, debug); - endif - - if !PARALLEL # ordinary serial version - points_per_node = nn; # do the all on this node - z = kernel_density_nodes(eval_points, data, do_cv, kernel, points_per_node, computenodes, debug); - else # parallel version - z = zeros(nn,1); - points_per_node = floor(nn/(NSLAVES + 1)); # number of obsns per slave - # The command that the slave nodes will execute - cmd=['z_on_node = kernel_density_nodes(eval_points, data, do_cv, kernel, points_per_node, computenodes, debug); ',... - 'MPI_Send(z_on_node, 0, TAG, NEWORLD);']; - - # send items to slaves - - NumCmds_Send({"eval_points", "data", "do_cv", "kernel", "points_per_node", "computenodes", "debug","cmd"}, {eval_points, data, do_cv, kernel, points_per_node, computenodes, debug, cmd}); - - # evaluate last block on master while slaves are busy - z_on_node = kernel_density_nodes(eval_points, data, do_cv, kernel, points_per_node, computenodes, debug); - startblock = NSLAVES*points_per_node + 1; - endblock = nn; - z(startblock:endblock,:) = z(startblock:endblock,:) + z_on_node; - - # collect slaves' results - z_on_node = zeros(points_per_node,1); # size may differ between master and compute nodes - reset here - for i = 1:NSLAVES - MPI_Recv(z_on_node,i,TAG,NEWORLD); - startblock = i*points_per_node - points_per_node + 1; - endblock = i*points_per_node; - z(startblock:endblock,:) = z(startblock:endblock,:) + z_on_node; - endfor - - # clean up after parallel - LAM_Finalize; - endif - z = z*det(H_inv); -endfunction
--- a/main/econometrics/inst/kernel_density_cvscore.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,23 +0,0 @@ -## Copyright (C) 2006 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## cvscore = kernel_density_cvscore(bandwidth, data, kernel) - -function cvscore = kernel_density_cvscore(bandwidth, data, kernel) - dens = kernel_density(data, data, exp(bandwidth), true, 0, 0, chol(cov(data)), kernel); - dens = dens + eps; # some kernels can assign zero density - cvscore = -mean(log(dens)); -endfunction -
--- a/main/econometrics/inst/kernel_example.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,140 +0,0 @@ -## Copyright (C) 2007 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## kernel_example: examples of how to use kernel density and regression functions -## requires the optim and plot packages from Octave Forge -## -## usage: kernel_example; - -# sample size (default n = 500) - should get better fit (on average) -# as this increases, supposing that you allow the optimal window width -# to be found, by uncommenting the relevant lines -n = 500; - -# set this to greater than 0 to try parallel computations (requires MPITB) -compute_nodes = 0; -nodes = compute_nodes + 1; # count master node - -close all; -hold off; - -############################################################ -# kernel regression example -# uniformly spaced data points on [0,2] -x = 1:n; -x = x'; -x = 2*x/n; -# generate dependent variable -trueline = x + (x.^2)/2 - 3.1*(x.^3)/3 + 1.2*(x.^4)/4; -sig = 0.5; -y = trueline + sig*randn(n,1); -tic; -fit = kernel_regression(x, y, x); # use the default bandwidth -t1 = toc; -printf("\n"); -printf("########################################################################\n"); -printf("time for kernel regression example using %d data points and %d compute nodes: %f\n", n, nodes, t1); -plot(x, fit, ";fit;", x, trueline,";true;"); -grid("on"); -title("Example 1: Kernel regression fit"); - -############################################################ -# kernel density example: univariate - fit to Chi^2(3) data -data = sumsq(randn(n,3),2); -# evaluation point are on a grid for plotting -stepsize = 0.2; -grid_x = (-1:stepsize:11)'; -bandwidth = 0.55; -# get optimal bandwidth (time consuming, uncomment if you want to try it) -# bandwidth = kernel_optimal_bandwidth(data); -# get the fitted density and do a plot -tic; -dens = kernel_density(grid_x, data, bandwidth, "kernel_normal", false, false, compute_nodes); -t1 = toc; -printf("\n"); -printf("########################################################################\n"); -printf("time for univariate kernel density example using %d data points and %d compute nodes: %f\n", n, nodes, t1); -printf("A rough integration under the fitted univariate density is %f\n", sum(dens)*stepsize); -figure(); -plot(grid_x, dens, ";fitted density;", grid_x, chi2pdf(grid_x,3), ";true density;"); -title("Example 2: Kernel density fit: Univariate Chi^2(3) data"); - -############################################################ -# kernel density example: bivariate -# X ~ N(0,1) -# Y ~ Chi squared(3) -# X, Y are dependent -d = randn(n,3); -data = [d(:,1) sumsq(d,2)]; -# evaluation points are on a grid for plotting -stepsize = 0.2; -a = (-5:stepsize:5)'; # for the N(0,1) -b = (-1:stepsize:9)'; # for the Chi squared(3) -gridsize = rows(a); -[grid_x, grid_y] = meshgrid(a, b); -eval_points = [vec(grid_x) vec(grid_y)]; -bandwidth = 0.85; -# get optimal bandwidth (time consuming, uncomment if you want to try it) -# bandwidth = kernel_optimal_bandwidth(data); -# get the fitted density and do a plot -tic; -dens = kernel_density(eval_points, data, bandwidth, "kernel_normal", false, false, compute_nodes); -t1 = toc; -printf("\n"); -printf("########################################################################\n"); -printf("time for multivariate kernel density example using %d data points and %d compute nodes: %f\n", n, nodes, t1); -dens = reshape(dens, gridsize, gridsize); -printf("A rough integration under the fitted bivariate density is %f\n", sum(sum(dens))*stepsize^2); -figure(); -surf(grid_x, grid_y, dens); -title("Example 3: Kernel density fit: dependent bivariate data"); -xlabel("true marginal density is N(0,1)"); -ylabel("true marginal density is Chi^2(3)"); -# more extensive test of parallel -if compute_nodes > 0 # only try this if parallel is available - ns =[4000; 8000; 10000; 12000; 16000; 20000]; - printf("\n"); - printf("########################################################################\n"); - printf("kernel regression example with several sample sizes serial/parallel timings\n"); - figure(); - clf; - title("Compute time versus nodes, kernel regression with different sample sizes"); - xlabel("nodes"); - ylabel("time (sec)"); - hold on; - ts = zeros(rows(ns),4); - for i = 1:rows(ns) - for compute_nodes = 0:3 - nodes = compute_nodes + 1; - n = ns(i,:); - x = 1:n; - x = x'; - x = 2*x/n; - # generate dependent variable - trueline = x + (x.^2)/2 - 3.1*(x.^3)/3 + 1.2*(x.^4)/4; - sig = 0.5; - y = trueline + sig*randn(n,1); - bandwidth = 0.45; - tic; - fit = kernel_regression(x, y, x, bandwidth, "kernel_normal", false, false, compute_nodes); - t1 = toc; - ts(i, nodes) = t1; - plot(nodes, t1, "*"); - printf(" %d data points and %d compute nodes: %f\n", n, nodes, t1); - endfor - plot(ts(i,:)'); - endfor - hold off; -endif
--- a/main/econometrics/inst/kernel_optimal_bandwidth.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,58 +0,0 @@ -## Copyright (C) 2007 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## kernel_optimal_bandwidth: find optimal bandwith doing leave-one-out cross validation -## inputs: -## * data: data matrix -## * depvar: column vector or empty (""). -## If empty, do kernel density, orherwise, kernel regression -## * kernel (optional, string) the kernel function to use -## output: -## * h: the optimal bandwidth - -function bandwidth = kernel_optimal_bandwidth(data, depvar, kernel) - - if (nargin < 2) error("kernel_optimal_bandwidth: 3 arguments required"); endif - if (nargin < 3) kernel = "kernel_epanechnikov"; endif - - do_density = false; - if isempty(depvar) do_density = true; endif; - - # SA controls - ub = 3; - lb = -5; - nt = 1; - ns = 1; - rt = 0.05; - maxevals = 50; - neps = 5; - functol = 1e-2; - paramtol = 1e-3; - verbosity = 0; - minarg = 1; - sa_control = { lb, ub, nt, ns, rt, maxevals, neps, functol, paramtol, verbosity, 1}; - - # bfgs controls - bfgs_control = {10}; - - if do_density - bandwidth = samin("kernel_density_cvscore", {1, data, kernel}, sa_control); - bandwidth = bfgsmin("kernel_density_cvscore", {bandwidth, data, kernel}, bfgs_control); - else - bandwidth = samin("kernel_regression_cvscore", {1, data, depvar, kernel}, sa_control); - bandwidth = bfgsmin("kernel_regression_cvscore", {bandwidth, data, depvar, kernel}, bfgs_control); - endif - bandwidth = exp(bandwidth); -endfunction
--- a/main/econometrics/inst/kernel_regression.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,116 +0,0 @@ -## Copyright (C) 2006 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## kernel_regression: kernel regression estimator -## -## usage: -## fit = kernel_regression(eval_points, depvar, condvars, bandwidth) -## -## inputs: -## eval_points: PxK matrix of points at which to calculate the density -## depvar: Nx1 vector of observations of the dependent variable -## condvars: NxK matrix of data points -## bandwidth (optional): positive scalar, the smoothing parameter. -## Default is N ^ (-1/(4+K)) -## kernel (optional): string. Name of the kernel function. Default is -## Gaussian kernel. -## prewhiten bool (optional): default true. If true, rotate data -## using Choleski decomposition of inverse of covariance, -## to approximate independence after the transformation, which -## makes a product kernel a reasonable choice. -## do_cv: bool (optional). default false. If true, calculate leave-1-out -## fit to calculate the cross validation score -## computenodes: int (optional, default 0). -## Number of compute nodes for parallel evaluation -## debug: bool (optional, default false). show results on compute nodes if doing -## a parallel run -## outputs: -## fit: Px1 vector: the fitted value at each of the P evaluation points. - -function z = kernel_regression(eval_points, depvar, condvars, bandwidth, kernel, prewhiten, do_cv, computenodes, debug) - - if nargin < 3; error("kernel_regression: at least 3 arguments are required"); endif - - n = rows(condvars); - k = columns(condvars); - - # set defaults for optional args - if (nargin < 4) bandwidth = (n ^ (-1/(4+k))); endif # bandwidth - see Li and Racine pg. 66 - if (nargin < 5) kernel = "kernel_normal"; endif # what kernel? - if (nargin < 6) prewhiten = true; endif # automatic prewhitening? - if (nargin < 7) do_cv = false; endif # ordinary or leave-1-out - if (nargin < 8) computenodes = 0; endif # parallel? - if (nargin < 9) debug = false; endif; # debug? - - - nn = rows(eval_points); - n = rows(depvar); - - if prewhiten - H = bandwidth*chol(cov(condvars)); - else - H = bandwidth; - endif - H_inv = inv(H); - - # weight by inverse bandwidth matrix - eval_points = eval_points*H_inv; - condvars = condvars*H_inv; - - data = [depvar condvars]; # put it all together for sending to nodes - - # check if doing this parallel or serial - global PARALLEL NSLAVES NEWORLD NSLAVES TAG - PARALLEL = 0; - - if computenodes > 0 - PARALLEL = 1; - NSLAVES = computenodes; - LAM_Init(computenodes, debug); - endif - - if !PARALLEL # ordinary serial version - points_per_node = nn; # do the all on this node - z = kernel_regression_nodes(eval_points, data, do_cv, kernel, points_per_node, computenodes, debug); - else # parallel version - z = zeros(nn,1); - points_per_node = floor(nn/(NSLAVES + 1)); # number of obsns per slave - # The command that the slave nodes will execute - cmd=['z_on_node = kernel_regression_nodes(eval_points, data, do_cv, kernel, points_per_node, computenodes, debug); ',... - 'MPI_Send(z_on_node, 0, TAG, NEWORLD);']; - - # send items to slaves - - NumCmds_Send({"eval_points", "data", "do_cv", "kernel", "points_per_node", "computenodes", "debug","cmd"}, {eval_points, data, do_cv, kernel, points_per_node, computenodes, debug, cmd}); - - # evaluate last block on master while slaves are busy - z_on_node = kernel_regression_nodes(eval_points, data, do_cv, kernel, points_per_node, computenodes, debug); - startblock = NSLAVES*points_per_node + 1; - endblock = nn; - z(startblock:endblock,:) = z(startblock:endblock,:) + z_on_node; - - # collect slaves' results - z_on_node = zeros(points_per_node,1); # size may differ between master and compute nodes - reset here - for i = 1:NSLAVES - MPI_Recv(z_on_node,i,TAG,NEWORLD); - startblock = i*points_per_node - points_per_node + 1; - endblock = i*points_per_node; - z(startblock:endblock,:) = z(startblock:endblock,:) + z_on_node; - endfor - - # clean up after parallel - LAM_Finalize; - endif -endfunction
--- a/main/econometrics/inst/kernel_regression_cvscore.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,22 +0,0 @@ -## Copyright (C) 2006 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## cvscore = kernel_regression_cvscore(bandwidth, data, depvar) - -function cvscore = kernel_regression_cvscore(bandwidth, data, depvar) - fit = kernel_regression(data, depvar, data, exp(bandwidth), true); - cvscore = norm(depvar - fit); -endfunction -
--- a/main/econometrics/inst/mle_estimate.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,73 +0,0 @@ -## Copyright (C) 2003, 2004, 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## usage: -## [theta, obj_value, conv, iters] = mle_estimate(theta, data, model, modelargs, control, nslaves) -## -## inputs: -## theta: column vector of model parameters -## data: data matrix -## model: name of function that computes log-likelihood -## modelargs: (cell) additional inputs needed by model. May be empty ("") -## control: (optional) BFGS or SA controls (see bfgsmin and samin). May be empty (""). -## nslaves: (optional) number of slaves if executed in parallel (requires MPITB) -## -## outputs: -## theta: ML estimated value of parameters -## obj_value: the value of the log likelihood function at ML estimate -## conv: return code from bfgsmin (1 means success, see bfgsmin for details) -## iters: number of BFGS iteration used -## -## please see mle_example.m for examples of how to use this - -function [theta, obj_value, convergence, iters] = mle_estimate(theta, data, model, modelargs, control, nslaves = 0) - - - if nargin < 3 - error("mle_estimate: 3 arguments required"); - endif - - if nargin < 4 modelargs = {}; endif # create placeholder if not used - if !iscell(modelargs) modelargs = {}; endif # default controls if receive placeholder - if nargin < 5 control = {-1,0,1,1}; endif # default controls and method - if !iscell(control) control = {-1,0,1,1}; endif # default controls if receive placeholder - if nslaves > 0 - global NSLAVES PARALLEL NEWORLD TAG; - LAM_Init(nslaves); - # Send the data to all nodes - NumCmds_Send({"data", "model", "modelargs"}, {data, model, modelargs}); - endif - - # bfgs or sa? - if (size(control,1)*size(control,2) == 0) # use default bfgs if no control - control = {Inf,0,1,1}; - method = "bfgs"; - elseif (size(control,1)*size(control,2) < 11) - method = "bfgs"; - else method = "sa"; - endif - - # do estimation using either bfgsmin or samin - if strcmp(method, "bfgs") - [theta, obj_value, convergence, iters] = bfgsmin("mle_obj", {theta, data, model, modelargs, nslaves}, control); - elseif strcmp(method, "sa") - [theta, obj_value, convergence] = samin("mle_obj", {theta, data, model, modelargs, nslaves}, control); - endif - - if nslaves > 0 - LAM_Finalize; - endif # cleanup - obj_value = - obj_value; # recover from minimization rather than maximization -endfunction
--- a/main/econometrics/inst/mle_example.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,77 +0,0 @@ -## Copyright (C) 2003, 2004 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## Example to show how to use MLE functions - -# Generate data -n = 1000; # how many observations? - -# the explanatory variables: note that they have unequal scales -x = [ones(n,1) -rand(n,1) randn(n,1)]; -theta = 1:3; # true coefficients are 1,2,3 -theta = theta'; - -lambda = exp(x*theta); -y = poissrnd(lambda); # generate the dependent variable - -#################################### -# define arguments for mle_results # -#################################### - -# starting values -theta = zeros(3,1); -# data -data = [y, x]; -# name of model to estimate -model = "poisson"; -modelargs = {0}; # if this is zero the function gives analytic score, otherwise not -# parameter names -names = char("beta1", "beta2", "beta3"); -mletitle = "Poisson MLE trial"; # title for the run - -# controls for bfgsmin: 30 iterations is not always enough for convergence -control = {50,0}; - -# This displays the results -printf("\n\nanalytic score, unscaled data\n"); -[theta, V, obj_value, infocrit] = mle_results(theta, data, model, modelargs, names, mletitle, 0, control); - -# This just calculates the results, no screen display -printf("\n\nanalytic score, unscaled data, no screen display\n"); -theta = zeros(3,1); -[theta, obj_value, convergence] = mle_estimate(theta, data, model, modelargs, control); -printf("obj_value = %f, to confirm it worked\n", obj_value); - -# This show how to scale data during estimation, but get results -# for data in original units (recommended to avoid conditioning problems) -# This usually converges faster, depending upon the data -printf("\n\nanalytic score, scaled data\n"); -[scaled_x, unscale] = scale_data(x); -data = [y, scaled_x]; -theta = zeros(3,1); -[theta, V, obj_value, infocrit] = mle_results(theta, data, model, modelargs, names, mletitle, unscale, control); - -# Example using numeric score -printf("\n\nnumeric score, scaled data\n"); -theta = zeros(3,1); -modelargs = {1}; # set the switch for no score -[theta, V, obj_value, infocrit] = mle_results(theta, data, model, modelargs, names, mletitle, unscale, control); - -# Example doing estimation in parallel on a cluster (requires MPITB) -# uncomment the following if you have MPITB installed -# theta = zeros(3,1); -# nslaves = 1; -# title = "MLE estimation done in parallel"; -# [theta, V, obj_value, infocrit] = mle_results(theta, data, model, modelargs, names, mletitle, unscale, control, nslaves);
--- a/main/econometrics/inst/mle_obj.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,62 +0,0 @@ -## Copyright (C) 2003, 2004, 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## usage: [obj_value, score] = mle_obj(theta, data, model, modelargs, nslaves) -## -## Returns the average log-likelihood for a specified model -## This is for internal use by mle_estimate - -function [obj_value, score] = mle_obj(theta, data, model, modelargs, nslaves = 0) - - n = rows(data); - - if nslaves > 0 - global NSLAVES PARALLEL NEWORLD NSLAVES TAG; - - nn = floor(n/(NSLAVES + 1)); # number of obsns per slave - - # The command that the slave nodes will execute - cmd=['contrib = mle_obj_nodes(theta, data, model, modelargs, nn); ',... - 'MPI_Send(contrib,0,TAG,NEWORLD);']; - - # send items to slaves - NumCmds_Send({"theta", "nn", "cmd"}, {theta, nn, cmd}); - - # evaluate last block on master while slaves are busy - obj_value = mle_obj_nodes(theta, data, model, modelargs, nn); - - # collect slaves' results - contrib = 0.0; # must be initialized to use MPI_Recv - for i = 1:NSLAVES - MPI_Recv(contrib,i,TAG,NEWORLD); - obj_value = obj_value + contrib; - endfor - - # compute the average - obj_value = - obj_value / n; - score = "na"; # fix this later to allow analytic score in parallel - - else # serial version - [contribs, score] = feval(model, theta, data, modelargs); - obj_value = - mean(contribs); - if isnumeric(score) score = - mean(score)'; endif # model passes "na" when score not available - endif - - # let's bullet-proof this in case the model goes nuts - if (((abs(obj_value) == Inf)) || (isnan(obj_value))) - obj_value = realmax/10; - endif - -endfunction
--- a/main/econometrics/inst/mle_obj_nodes.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,35 +0,0 @@ -## Copyright (C) 2003, 2004, 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## contrib = mle_obj_nodes(theta, data, model, modelargs, nn) - -function contrib = mle_obj_nodes(theta, data, model, modelargs, nn) - global NEWORLD NSLAVES - - # Who am I? - [info, rank] = MPI_Comm_rank(NEWORLD); - if rank == 0 # Do this if I'm master - startblock = NSLAVES*nn + 1; - endblock = rows(data); - else # this is for the slaves - startblock = rank*nn-nn+1; - endblock = rank*nn; - endif - - data = data(startblock:endblock,:); - contrib = feval(model, theta, data, modelargs); - contrib = sum(contrib); - -endfunction
--- a/main/econometrics/inst/mle_results.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,87 +0,0 @@ -## Copyright (C) 2003, 2004, 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## usage: [theta, V, obj_value, infocrit] = -## mle_results(theta, data, model, modelargs, names, title, unscale, control) -## -## inputs: -## theta: column vector of model parameters -## data: data matrix -## model: name of function that computes log-likelihood -## modelargs: (cell) additional inputs needed by model. May be empty ("") -## names: vector of parameter names, e.g., use names = char("param1", "param2"); -## title: string, describes model estimated -## unscale: (optional) cell that holds means and std. dev. of data (see scale_data) -## control: (optional) BFGS or SA controls (see bfgsmin and samin). May be empty (""). -## nslaves: (optional) number of slaves if executed in parallel (requires MPITB) -## -## outputs: -## theta: ML estimated value of parameters -## obj_value: the value of the log likelihood function at ML estimate -## conv: return code from bfgsmin (1 means success, see bfgsmin for details) -## iters: number of BFGS iteration used -## -## Please see mle_example for information on how to use this - -# report results -function [theta, V, obj_value, infocrit] = mle_results(theta, data, model, modelargs, names, mletitle, unscale, control = {-1}, nslaves = 0) - if nargin < 6 mletitle = "Generic MLE title"; endif - - [theta, obj_value, convergence] = mle_estimate(theta, data, model, modelargs, control, nslaves); - V = mle_variance(theta, data, model, modelargs); - - # unscale results if argument has been passed - # this puts coefficients into scale corresponding to the original modelargs - if (nargin > 6) - if iscell(unscale) # don't try it if unscale is simply a placeholder - [theta, V] = unscale_parameters(theta, V, unscale); - endif - endif - - [theta, V] = delta_method("parameterize", theta, {data, model, modelargs}, V); - - n = rows(data); - k = rows(V); - se = sqrt(diag(V)); - if convergence == 1 convergence="Normal convergence"; - elseif convergence == 2 convergence="No convergence"; - elseif convergence == -1 convergence = "Max. iters. exceeded"; - endif - printf("\n\n******************************************************\n"); - disp(mletitle); - printf("\nMLE Estimation Results\n"); - printf("BFGS convergence: %s\n\n", convergence); - - printf("Average Log-L: %f\n", obj_value); - printf("Observations: %d\n", n); - a =[theta, se, theta./se, 2 - 2*normcdf(abs(theta ./ se))]; - - clabels = char("estimate", "st. err", "t-stat", "p-value"); - - printf("\n"); - if names !=0 prettyprint(a, names, clabels); - else prettyprint_c(a, clabels); - endif - - printf("\nInformation Criteria \n"); - caic = -2*n*obj_value + rows(theta)*(log(n)+1); - bic = -2*n*obj_value + rows(theta)*log(n); - aic = -2*n*obj_value + 2*rows(theta); - infocrit = [caic, bic, aic]; - printf("CAIC : %8.4f Avg. CAIC: %8.4f\n", caic, caic/n); - printf(" BIC : %8.4f Avg. BIC: %8.4f\n", bic, bic/n); - printf(" AIC : %8.4f Avg. AIC: %8.4f\n", aic, aic/n); - printf("******************************************************\n"); -endfunction
--- a/main/econometrics/inst/nls_estimate.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,71 +0,0 @@ -## Copyright (C) 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## usage: -## [theta, obj_value, conv, iters] = nls_estimate(theta, data, model, modelargs, control, nslaves) -## -## inputs: -## theta: column vector of model parameters -## data: data matrix -## model: name of function that computes the vector of sums of squared errors -## modelargs: (cell) additional inputs needed by model. May be empty ("") -## control: (optional) BFGS or SA controls (see bfgsmin and samin). May be empty (""). -## nslaves: (optional) number of slaves if executed in parallel (requires MPITB) -## -## outputs: -## theta: NLS estimated value of parameters -## obj_value: the value of the sum of squared errors at NLS estimate -## conv: return code from bfgsmin (1 means success, see bfgsmin for details) -## iters: number of BFGS iteration used -## -## please see nls_example.m for examples of how to use this - -function [theta, obj_value, convergence, iters] = nls_estimate(theta, data, model, modelargs, control, nslaves) - - if nargin < 3 - error("nls_estimate: 3 arguments required"); - endif - - if nargin < 4 modelargs = {}; endif # create placeholder if not used - if !iscell(modelargs) modelargs = {}; endif # default controls if receive placeholder - if nargin < 5 control = {Inf,0,1,1}; endif # default controls and method - if !iscell(control) control = {Inf,0,1,1}; endif # default controls if receive placeholder - if nargin < 6 nslaves = 0; endif - - if nslaves > 0 - global NSLAVES PARALLEL NEWORLD TAG - LAM_Init(nslaves); - # Send the data to all nodes - NumCmds_Send({"data", "model", "modelargs"}, {data, model, modelargs}); - endif - - # bfgs or sa? - if (size(control,1)*size(control,2) == 0) # use default bfgs if no control - control = {Inf,0,1,1}; - method = "bfgs"; - elseif (size(control,1)*size(control,2) < 11) - method = "bfgs"; - else method = "sa"; - endif - - if strcmp(method, "bfgs") - [theta, obj_value, convergence, iters] = bfgsmin("nls_obj", {theta, data, model, modelargs, nslaves}, control); - elseif strcmp(method, "sa") - [theta, obj_value, convergence] = samin("nls_obj", {theta, data, model, modelargs, nslaves}, control); - endif - - # cleanup - if nslaves > 0 LAM_Finalize; endif -endfunction
--- a/main/econometrics/inst/nls_example.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,57 +0,0 @@ -## Copyright (C) 2006 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## Example to show how to use NLS - -# Generate data -n = 100; # how many observations? - -# the explanatory variables: note that they have unequal scales -x = [ones(n,1) rand(n,2)]; -theta = 1:3; # true coefficients are 1,2,3 -theta = theta'; - -lambda = exp(x*theta); -y = randp(lambda); # generate the dependent variable - -# example objective function for nls -function [obj_contrib, score] = nls_example_obj(theta, data, otherargs) - y = data(:,1); - x = data(:,2:columns(data)); - lambda = exp(x*theta); - errors = y - lambda; - obj_contrib = errors .* errors; - score = "na"; -endfunction - - -##################################### -# define arguments for nls_estimate # -##################################### -# starting values -theta = zeros(3,1); -# data -data = [y, x]; -# name of model to estimate -model = "nls_example_obj"; -modelargs = {}; # none required for this obj fn. -# controls for bfgsmin - limit to 50 iters, and print final results -control = {50,1}; - -#################################### -# do the estimation # -#################################### -printf("\nNLS estimation example\n"); -[theta, obj_value, convergence] = nls_estimate(theta, data, model, modelargs, control);
--- a/main/econometrics/inst/nls_obj.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,59 +0,0 @@ -## Copyright (C) 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## usage: [obj_value, score] = nls_obj(theta, data, model, modelargs, nslaves) -## -## Returns the average sum of squared errors for a specified model -## This is for internal use by nls_estimate - -function [obj_value, score] = nls_obj(theta, data, model, modelargs, nslaves) - - n = rows(data); - - if nslaves > 0 - global NEWORLD NSLAVES TAG - nn = floor(n/(NSLAVES + 1)); # number of obsns per slave - - # The command that the slave nodes will execute - cmd=['contrib = nls_obj_nodes(theta, data, model, modelargs, nn); ',... - 'MPI_Send(contrib,0,TAG,NEWORLD);']; - - # send items to slaves - NumCmds_Send({"theta", "nn", "cmd"}, {theta, nn, cmd}); - - # evaluate last block on master while slaves are busy - obj_value = nls_obj_nodes(theta, data, model, modelargs, nn); - - # collect slaves' results - contrib = 0.0; # must be initialized to use MPI_Recv - for i = 1:NSLAVES - MPI_Recv(contrib,i,TAG,NEWORLD); - obj_value = obj_value + contrib; - endfor - - # compute the average - obj_value = obj_value / n; - score = "na"; # fix this later to allow analytic score in parallel - - else # serial version - [contribs, score] = feval(model, theta, data, modelargs); - obj_value = mean(contribs); - if isnumeric(score) score = mean(score)'; endif # model passes "na" when score not available - endif - - # let's bullet-proof this in case the model goes nuts - if (((abs(obj_value) == Inf)) || (isnan(obj_value))) obj_value = realmax; endif - -endfunction
--- a/main/econometrics/inst/parameterize.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,27 +0,0 @@ -## Copyright (C) 2003, 2004 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## usage: theta = parameterize(theta, otherargs) -## -## This is an empty function, provided so that -## delta_method will work as is. Replace it with -## the parameter transformations your models use. -## Note: you can let "otherargs" contain the model -## name so that this function can do parameterizations -## for a variety of models - -function theta = parameterize(theta, otherargs) - -endfunction
--- a/main/econometrics/inst/poisson.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,25 +0,0 @@ -## Copyright (C) 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## Example likelihood function (Poisson for count data) with score - -function [log_density, score] = poisson(theta, data, otherargs) - y = data(:,1); - x = data(:,2:columns(data)); - lambda = exp(x*theta); - log_density = -lambda + y .* (x*theta) - lgamma(y+1); - score = diag (y - lambda) * x; - if (otherargs{1} == 1) score = "na"; endif # provide analytic score or not? -endfunction
--- a/main/econometrics/inst/poisson_moments.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,26 +0,0 @@ -## Copyright (C) 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## the form a user-written moment function should take - -function m = poisson_moments(theta, data, momentargs) - k = momentargs{1}; # use this so that data can hold dep, indeps, and instr - y = data(:,1); - x = data(:,2:k+1); - w = data(:, k+2:columns(data)); - lambda = exp(x*theta); - e = y ./ lambda - 1; - m = diag(e) * w; -endfunction
--- a/main/econometrics/inst/prettyprint.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,48 +0,0 @@ -## Copyright (C) 2003, 2004 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## this prints matrices with row and column labels - -function prettyprint(mat, rlabels, clabels) - - # left pad the column labels - a = columns(rlabels); - for i = 1:a - printf(" "); - endfor - printf(" "); - - # print the column labels - clabels = [" ";clabels]; # pad to 8 characters wide - clabels = strjust(clabels,"right"); - - k = columns(mat); - for i = 1:k - printf("%s ",clabels(i+1,:)); - endfor - - # now print the row labels and rows - printf("\n"); - k = rows(mat); - for i = 1:k - if ischar(rlabels(i,:)) - printf(rlabels(i,:)); - else - printf("%i", rlabels(i,:)); - endif - printf(" %10.3f", mat(i,:)); - printf("\n"); - endfor -endfunction
--- a/main/econometrics/inst/prettyprint_c.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,37 +0,0 @@ -## Copyright (C) 2003, 2004 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## this prints matrices with column labels but no row labels -function prettyprint_c(mat, clabels) - - printf(" "); - - # print the column labels - clabels = [" ";clabels]; # pad to 8 characters wide - clabels = strjust(clabels,"right"); - - k = columns(mat); - for i = 1:k - printf("%s ",clabels(i+1,:)); - endfor - - # now print the row labels and rows - printf("\n"); - k = rows(mat); - for i = 1:k - printf(" %8.3f", mat(i,:)); - printf("\n"); - endfor -endfunction
--- a/main/econometrics/inst/private/average_moments.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,53 +0,0 @@ -## Copyright (C) 2003, 2004, 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## for internal use by gmm_estimate - -## average moments (separate function so it can be differentiated) -function m = average_moments(theta, data, moments, momentargs) - - global NSLAVES PARALLEL NEWORLD NSLAVES TAG; - - n = rows(data); - - if PARALLEL - nn = floor(n/(NSLAVES + 1)); # save some work for master - - # The command that the slave nodes will execute - cmd=['contrib = sum_moments_nodes(theta, data, moments, momentargs, nn); ',... - 'MPI_Send(contrib,0,TAG,NEWORLD);']; - - # send items to slaves - NumCmds_Send({"theta", "nn", "cmd"},{theta, nn, cmd}); - - # evaluate last block on master while slaves are busy - m = feval("sum_moments_nodes", theta, data, moments, momentargs, nn); - - # collect slaves' results - contrib = zeros(1,columns(m)); - for i = 1:NSLAVES - MPI_Recv(contrib,i,TAG,NEWORLD); - m = m + contrib; - endfor - - m = m'; # we want a column vector, please - m = m/n; # average please, not sum - - else # serial version - m = feval(moments, theta, data, momentargs); - m = mean(m)'; # returns Gx1 moment vector - endif - -endfunction
--- a/main/econometrics/inst/private/kernel_density_nodes.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,53 +0,0 @@ -## Copyright (C) 2006, 2007 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## kernel_density_nodes: for internal use by kernel_density - does calculations on nodes - -function z = kernel_density_nodes(eval_points, data, do_cv, kernel, points_per_node, nslaves, debug) - - if (nslaves > 0) - global NEWORLD - [info, myrank] = MPI_Comm_rank(NEWORLD); - else myrank = 0; # if not parallel then do all on master node - endif - - if myrank == 0 # Do this if I'm master - startblock = nslaves*points_per_node + 1; - endblock = rows(eval_points); - else # this is for the slaves - startblock = myrank*points_per_node - points_per_node + 1; - endblock = myrank*points_per_node; - endif - - # the block of eval_points this node does - myeval = eval_points(startblock:endblock,:); - nn = rows(myeval); - n = rows(data); - - W = __kernel_weights(data, myeval, kernel); - if (do_cv) - W = W - diag(diag(W)); - z = sum(W,2) / (n-1); - else - z = sum(W,2) / n; - endif - - if debug - printf("z on node %d: \n", myrank); - z' - endif -endfunction - -
--- a/main/econometrics/inst/private/kernel_epanechnikov.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,35 +0,0 @@ -## Copyright (C) 2006 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## kernel_epanechnikov: this function is for internal use by kernel_density -## and kernel_regression -## -## multivariate spherical Epanechnikov kernel -## input: PxK matrix - P data points, each of which is in R^K -## output: Px1 vector, input matrix passed though the kernel -## other multivariate kernel functions should follow this convention - -function z = kernel_epanechnikov(z) - - K = columns(z); - - # Volume of d-dimensional unit sphere - c = pi ^ (K/2) / gamma(K/2 + 1); - - # compute kernel - z = sumsq(z, 2); - z = ((1/2) / c * (K + 2) * (1 - z)) .* (z < 1); - -endfunction
--- a/main/econometrics/inst/private/kernel_normal.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,29 +0,0 @@ -## Copyright (C) 2006 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## kernel_normal: this function is for internal use by kernel_density -## and kernel_regression -## -## product normal kernel -## input: PxK matrix - P data points, each of which is in R^K -## output: Px1 vector, input matrix passed though the kernel -## other multivariate kernel functions should follow this convention - -function z = kernel_normal(z) - - z = normpdf(z); - z = prod(z,2); - -endfunction
--- a/main/econometrics/inst/private/kernel_regression_nodes.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,61 +0,0 @@ -## Copyright (C) 2006, 2007 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## kernel_regression_nodes: for internal use by kernel_regression - does calculations on nodes - -function z = kernel_regression_nodes(eval_points, data, do_cv, kernel, points_per_node, nslaves, debug) - - if (nslaves > 0) - global NEWORLD - [info, myrank] = MPI_Comm_rank(NEWORLD); - else myrank = 0; # if not parallel then do all on master node - endif - - if myrank == 0 # Do this if I'm master - startblock = nslaves*points_per_node + 1; - endblock = rows(eval_points); - else # this is for the slaves - startblock = myrank*points_per_node - points_per_node + 1; - endblock = myrank*points_per_node; - endif - - # the block of eval_points this node does - myeval = eval_points(startblock:endblock,:); - nn = rows(myeval); - n = rows(data); - - y = data(:,1); - data = data(:,2:columns(data)); - W = __kernel_weights(data, myeval, kernel); - - # drop own weight for CV - if (do_cv) W = W - diag(diag(W)); endif - - den = sum(W,2); - if !all(den) - warning("kernel_regression: some evaluation points have no neighbors - increase the bandwidth"); - den = den + eps; # avoid divide by zero - endif - - W = W ./ (repmat(den,1,n)); - z = W*y; - - if debug - printf("z on node %d: \n", myrank); - z' - endif -endfunction - -
--- a/main/econometrics/inst/private/mle_variance.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,29 +0,0 @@ -## Copyright (C) 2003, 2004, 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## usage: [V,scorecontribs,J_inv] = -## mle_variance(theta, data, model, modelargs) -## -## This is for internal use by mle_results - -# sandwich form of var-cov matrix -function [V, scorecontribs, J_inv] = mle_variance(theta, data, model, modelargs) - scorecontribs = numgradient(model, {theta, data, modelargs}); - n = rows(scorecontribs); - I = scorecontribs'*scorecontribs / n; - J = numhessian("mle_obj", {theta, data, model, modelargs}); - J_inv = inverse(J); - V = J_inv*I*J_inv/n; -endfunction
--- a/main/econometrics/inst/private/nls_obj_nodes.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,35 +0,0 @@ -## Copyright (C) 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## This is for internal use by nls_estimate - -function contrib = nls_obj_nodes(theta, data, model, modelargs, nn) - global NEWORLD NSLAVES - # Who am I? - [info, rank] = MPI_Comm_rank(NEWORLD); - - if rank == 0 # Do this if I'm master - startblock = NSLAVES*nn + 1; - endblock = rows(data); - else # this is for the slaves - startblock = rank*nn-nn+1; - endblock = rank*nn; - endif - - data = data(startblock:endblock,:); - contrib = feval(model, theta, data, modelargs); - contrib = sum(contrib); - -endfunction
--- a/main/econometrics/inst/private/sum_moments_nodes.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,37 +0,0 @@ -## Copyright (C) 2005 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## for internal use by gmm_estimate - -function contrib = sum_moments_nodes(theta, data, moments, momentargs, nn) - - global NEWORLD NSLAVES - - # Who am I? - [info, rank] = MPI_Comm_rank(NEWORLD); - - if rank == 0 # Do this if I'm master - startblock = NSLAVES*nn + 1; - endblock = rows(data); - else # this is for the slaves - startblock = rank*nn-nn+1; - endblock = rank*nn; - endif - - data = data(startblock:endblock,:); - contrib = feval(moments, theta, data, momentargs); - contrib = sum(contrib); - -endfunction
--- a/main/econometrics/inst/scale_data.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,45 +0,0 @@ -## Copyright (C) 2003, 2004 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## Standardizes and normalizes data matrix, -## primarily for use by BFGS - -function [zz, scalecoefs] = scale_data(z); - - n = rows(z); - k = columns(z); - - # Scale data - s = std(z)'; - test = s != 0; - s = s + (1 - test); # don't scale if column is a constant (avoid div by zero) - A = diag(1 ./ s); - - # De-mean all variables except constant, if a constant is present - test = std(z(:,1)) != 0; - if test - bb = zeros(n,k); - b = zeros(k,1); - else - b = -mean(z)'; - test = std(z)' != 0; - # don't take out mean if the column is a constant, to preserve identification - b = b .* test; - b = A*b; - bb = (diag(b) * ones(k,n))'; - endif - zz = z*A + bb; - scalecoefs = {A,b}; -endfunction
--- a/main/econometrics/inst/unscale_parameters.m Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,40 +0,0 @@ -## Copyright (C) 2003, 2004 Michael Creel <michael.creel@uab.es> -## -## This program is free software; you can redistribute it and/or modify it under -## the terms of the GNU General Public License as published by the Free Software -## Foundation; either version 3 of the License, or (at your option) any later -## version. -## -## This program is distributed in the hope that it will be useful, but WITHOUT -## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -## details. -## -## You should have received a copy of the GNU General Public License along with -## this program; if not, see <http://www.gnu.org/licenses/>. - -## Unscales parameters that were estimated using scaled data -## primarily for use by BFGS - -function [theta_us, vartheta_us] = unscale_parameters(theta, vartheta, scalecoefs); - k = rows(theta); - A = scalecoefs {1}; - b = scalecoefs {2}; - - kk = rows(b); - B = zeros(kk-1,kk); - B = [b'; B]; - - C = A + B; - - # allow for parameters that aren't associated with x - if (k > kk) - D = zeros(kk, k - kk); - C = [C, D; D', eye(k - kk)]; - endif; - - - - theta_us = C*theta; - vartheta_us = C * vartheta * C'; -endfunction
--- a/main/econometrics/src/Makefile Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,11 +0,0 @@ -MKOCTFILE = mkoctfile -Wall - -PROGS = $(patsubst %.cc,%.oct,$(wildcard *.cc)) - -all: $(PROGS) - -%.oct: %.cc - $(MKOCTFILE) $< - -clean: - rm -f *.o octave-core core *.oct *~
--- a/main/econometrics/src/__kernel_weights.cc Mon Jun 17 20:31:16 2013 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,60 +0,0 @@ -// Copyright (C) 2007 Michael Creel <michael.creel@uab.es> -// -// This program is free software; you can redistribute it and/or modify it under -// the terms of the GNU General Public License as published by the Free Software -// Foundation; either version 3 of the License, or (at your option) any later -// version. -// -// This program is distributed in the hope that it will be useful, but WITHOUT -// ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or -// FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more -// details. -// -// You should have received a copy of the GNU General Public License along with -// this program; if not, see <http://www.gnu.org/licenses/>. - -// __kernel_weights: for internal use by kernel density and regression functions -// This function was originally written as .m file and eventually rewritten in -// C++ for performance. the .m file was removed from the package on revision -// 10407 by carandraug - -#include <oct.h> -#include <octave/parse.h> - -DEFUN_DLD(__kernel_weights, args, ,"__kernel_weights: for internal use by kernel_regression and kernel_density functions") -{ - - Matrix data (args(0).matrix_value()); - Matrix evalpoints (args(1).matrix_value()); - std::string kernel (args(2).string_value()); - - int n, nn, i, j, k, dim; - - n = data.rows(); - dim = data.columns(); - nn = evalpoints.rows(); - Matrix W(nn, n); - Matrix zz(n,dim); - Matrix zzz; - octave_value kernelargs; - octave_value_list f_return; - - for (i = 0; i < nn; i++) { - for (j = 0; j < n; j++) { - // note to self: zz.insert(data.row(j) - evalpoints.row(i), j, 0) is slower - for (k = 0; k < dim; k++) { - zz(j,k) = data(j,k) - evalpoints(i,k); - } - } - kernelargs = zz; - f_return = feval(kernel, kernelargs); - zzz = f_return(0).matrix_value(); - - // note to self: W.insert(zzz.transpose(),i,0) is slower - for (j = 0; j < n; j++) { - W(i,j) = zzz(j,0); - } - } - f_return(0) = W; - return f_return; -}