--- a/main/statistics/INDEX	Sun Apr 20 13:49:11 2014 +0000
+++ b/main/statistics/INDEX	Thu Apr 24 20:04:16 2014 +0000
@@ -72,6 +72,7 @@
 Hypothesis testing
  anderson_darling_test
  runstest
+ signtest
  ttest
  ttest2
  vartest

--- a/main/statistics/NEWS	Sun Apr 20 13:49:11 2014 +0000
+++ b/main/statistics/NEWS	Thu Apr 24 20:04:16 2014 +0000
@@ -9,7 +9,7 @@
 
  ** The following functions are new:
  
-    cdf ttest ttest2 vartest vartest2 ztest
+    cdf signtest ttest ttest2 vartest vartest2 ztest
 
 Summary of important user-visible changes for statistics 1.2.3:
 -------------------------------------------------------------------

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/main/statistics/inst/signtest.m	Thu Apr 24 20:04:16 2014 +0000
@@ -0,0 +1,171 @@
+## Copyright (C) 2014 Tony Richardson
+##
+## 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/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} 
+## {[@var{pval}, @var{h}, @var{stats} ] =} 
+## signtest (@var{x})
+##
+## {[@var{pval}, @var{h}, @var{stats} ] =} 
+## signtest (@var{x}, @var{m})
+##
+## {[@var{pval}, @var{h}, @var{stats} ] =} 
+## signtest (@var{x}, @var{y})
+##
+## {[@var{pval}, @var{h}, @var{stats} ] =} 
+## signtest (@var{x}, @var{y}, @var{Name}, @var{Value})
+##
+## Perform a signtest of the null hypothesis that X is from a distribution
+## that has a zero median.
+##
+## If the second argument @var{m} is a scalar, the null hypothesis is that
+## X has median m.
+##
+## If the second argument @var{y} is a vector, the null hypothesis is that
+## the distribution of X - Y has zero median.
+##
+## The argument @var{alpha} can be used to specify the significance level
+## of the test (the default value is 0.05).  The string
+## argument @var{tail}, can be used to select the desired alternative
+## hypotheses.  If @var{alt} is @qcode{"both"} (default) the null is 
+## tested against the two-sided alternative @code{median (@var{x}) != @var{m}}.
+## If @var{alt} is @qcode{"right"} the one-sided 
+## alternative @code{median (@var{x}) > @var{m}} is considered.
+## Similarly for @qcode{"left"}, the one-sided alternative @code{median
+## (@var{x}) < @var{m}} is considered.  When @var{method} is 'exact'
+## the p-value is computed using an exact method (this is the default).  When
+## @var{method} is 'approximate' a normal approximation is used for the
+## test statistic.
+##
+## The p-value of the test is returned in @var{pval}. If @var{h} is 0 the 
+## null hypothesis is accepted, if it is 1 the null hypothesis is rejected. 
+## @var{stats} is a structure containing the value of the test statistic
+## (@var{sign}) and the value of the z statistic (@var{zval}) (only computed
+## when the 'method' is 'approximate'.
+##
+## @end deftypefn
+
+## Author: Tony Richardson <richardson.tony@gmail.com>
+## Description: Test for median
+
+function [p, h, stats] = signtest(x, my, varargin)
+  
+  my_default = 0;
+  alpha = 0.05;
+  tail  = 'both';
+  method = 'exact';
+
+  % Find the first non-singleton dimension of x
+  dim = min(find(size(x)~=1));
+  if isempty(dim), dim = 1; end
+
+  if (nargin == 1)
+    my = my_default;
+  end 
+  
+  i = 1;
+  while ( i <= length(varargin) )
+    switch lower(varargin{i})
+      case 'alpha'
+        i = i + 1;
+        alpha = varargin{i};
+      case 'tail'
+        i = i + 1;
+        tail = varargin{i};
+      case 'method'
+        i = i + 1;
+        method = varargin{i};
+      case 'dim'
+        i = i + 1;
+        dim = varargin{i};
+      otherwise
+        error('Invalid Name argument.',[]);
+    end
+    i = i + 1;
+  end
+  
+  if ~isa(tail, 'char')
+    error('tail argument to signtest must be a string\n',[]);
+  end
+
+  if ~isa(method, 'char')
+    error('method argument to signtest must be a string\n',[]);
+  end
+
+  % Set default values if arguments are present but empty
+  if isempty(my)
+    my = my_default;
+  end
+
+  % This adjustment allows everything else to remain the
+  % same for both the one-sample t test and paired tests.
+  % If second argument is a vector
+  if ~isscalar(my)
+    x = x - my;
+    my = my_default;
+  end  
+
+  n = size(x, dim);
+
+  switch lower(method)
+    case 'exact'
+      stats.zval = nan;
+      switch lower(tail)
+        case 'both'
+          w = min(sum(x<my),sum(x>my));
+          pl = binocdf(w, n, 0.5);
+          p = 2*min(pl,1-pl);
+        case 'left'
+          w = sum(x<my);
+          p = binocdf(w, n, 0.5);
+        case 'right'
+          w = sum(x>my);
+          p = 1 - binocdf(w, n, 0.5);
+        otherwise
+          error('Invalid tail argument to signtest\n',[]);
+      end
+    case 'approximate'
+      switch lower(tail)
+        case 'both'
+          npos = sum(x>my);
+          nneg = sum(x<my);
+          w = min(npos,nneg);
+          stats.zval = (w - 0.5*n - 0.5*sign(npos-nneg))/sqrt(0.25*n);
+          pl = normcdf(stats.zval);
+          p = 2*min(pl,1-pl);
+        case 'left'
+          npos = sum(x>my);
+          nneg = sum(x<my);
+          w = sum(x<my);
+          stats.zval = (w - 0.5*n - 0.5*sign(npos-nneg))/sqrt(0.25*n);
+          p = normcdf(stats.zval);
+        case 'right'
+          npos = sum(x>my);
+          nneg = sum(x<my);
+          w = sum(x>my);
+          stats.zval = (w - 0.5*n - 0.5*sign(npos-nneg))/sqrt(0.25*n);
+          p = 1-normcdf(stats.zval);
+        otherwise
+          error('Invalid tail argument to signtest\n',[]);
+      end
+    otherwise
+      error('Invalid method argument to signtest\n',[]);
+  end
+
+  stats.sign = w;
+  
+  h = double(p < alpha);  
+  
+end