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doc: Update more docstrings to have one sentence summary as first line. Reviewed optimization, polynomial, signal script directories. * scripts/optimization/fminbnd.m, scripts/optimization/fminsearch.m, scripts/optimization/fminunc.m, scripts/optimization/fsolve.m, scripts/optimization/fzero.m, scripts/optimization/glpk.m, scripts/optimization/lsqnonneg.m, scripts/optimization/pqpnonneg.m, scripts/optimization/qp.m, scripts/optimization/sqp.m, scripts/polynomial/compan.m, scripts/polynomial/mkpp.m, scripts/polynomial/mpoles.m, scripts/polynomial/pchip.m, scripts/polynomial/poly.m, scripts/polynomial/polyaffine.m, scripts/polynomial/polyder.m, scripts/polynomial/polyeig.m, scripts/polynomial/polyfit.m, scripts/polynomial/polygcd.m, scripts/polynomial/polyint.m, scripts/polynomial/polyout.m, scripts/polynomial/polyval.m, scripts/polynomial/ppder.m, scripts/polynomial/ppint.m, scripts/polynomial/ppjumps.m, scripts/polynomial/ppval.m, scripts/polynomial/residue.m, scripts/polynomial/roots.m, scripts/polynomial/spline.m, scripts/polynomial/splinefit.m, scripts/polynomial/unmkpp.m, scripts/signal/arch_fit.m, scripts/signal/arch_rnd.m, scripts/signal/arma_rnd.m, scripts/signal/autoreg_matrix.m, scripts/signal/bartlett.m, scripts/signal/blackman.m, scripts/signal/detrend.m, scripts/signal/diffpara.m, scripts/signal/durbinlevinson.m, scripts/signal/fftconv.m, scripts/signal/fftfilt.m, scripts/signal/fftshift.m, scripts/signal/filter2.m, scripts/signal/freqz.m, scripts/signal/hamming.m, scripts/signal/hanning.m, scripts/signal/hurst.m, scripts/signal/ifftshift.m, scripts/signal/periodogram.m, scripts/signal/sinc.m, scripts/signal/sinetone.m, scripts/signal/sinewave.m, scripts/signal/spectral_adf.m, scripts/signal/spectral_xdf.m, scripts/signal/spencer.m, scripts/signal/stft.m, scripts/signal/synthesis.m, scripts/signal/unwrap.m, scripts/signal/yulewalker.m: Update more docstrings to have one sentence summary as first line.
author Rik <rik@octave.org>
date Mon, 04 May 2015 21:50:57 -0700
parents 4197fc428c7d
children
comparison
equal deleted inserted replaced
20199:df437a52bcaf 20200:f1d0f506ee78
20 ## @deftypefn {Function File} {@var{p} =} polyfit (@var{x}, @var{y}, @var{n}) 20 ## @deftypefn {Function File} {@var{p} =} polyfit (@var{x}, @var{y}, @var{n})
21 ## @deftypefnx {Function File} {[@var{p}, @var{s}] =} polyfit (@var{x}, @var{y}, @var{n}) 21 ## @deftypefnx {Function File} {[@var{p}, @var{s}] =} polyfit (@var{x}, @var{y}, @var{n})
22 ## @deftypefnx {Function File} {[@var{p}, @var{s}, @var{mu}] =} polyfit (@var{x}, @var{y}, @var{n}) 22 ## @deftypefnx {Function File} {[@var{p}, @var{s}, @var{mu}] =} polyfit (@var{x}, @var{y}, @var{n})
23 ## Return the coefficients of a polynomial @var{p}(@var{x}) of degree 23 ## Return the coefficients of a polynomial @var{p}(@var{x}) of degree
24 ## @var{n} that minimizes the least-squares-error of the fit to the points 24 ## @var{n} that minimizes the least-squares-error of the fit to the points
25 ## @code{[@var{x}, @var{y}]}. If @var{n} is a logical vector, it is used 25 ## @code{[@var{x}, @var{y}]}.
26 ## as a mask to selectively force the corresponding polynomial 26 ##
27 ## coefficients to be used or ignored. 27 ## If @var{n} is a logical vector, it is used as a mask to selectively force
28 ## the corresponding polynomial coefficients to be used or ignored.
28 ## 29 ##
29 ## The polynomial coefficients are returned in a row vector. 30 ## The polynomial coefficients are returned in a row vector.
30 ## 31 ##
31 ## The optional output @var{s} is a structure containing the following fields: 32 ## The optional output @var{s} is a structure containing the following fields:
32 ## 33 ##
52 ## The values of the polynomial for each value of @var{x}. 53 ## The values of the polynomial for each value of @var{x}.
53 ## @end table 54 ## @end table
54 ## 55 ##
55 ## The second output may be used by @code{polyval} to calculate the 56 ## The second output may be used by @code{polyval} to calculate the
56 ## statistical error limits of the predicted values. In particular, the 57 ## statistical error limits of the predicted values. In particular, the
57 ## standard deviation of @var{p} coefficients is given by @* 58 ## standard deviation of @var{p} coefficients is given by
59 ##
58 ## @code{sqrt (diag (s.C)/s.df)*s.normr}. 60 ## @code{sqrt (diag (s.C)/s.df)*s.normr}.
59 ## 61 ##
60 ## When the third output, @var{mu}, is present the 62 ## When the third output, @var{mu}, is present the coefficients, @var{p}, are
61 ## coefficients, @var{p}, are associated with a polynomial in 63 ## associated with a polynomial in
62 ## @var{xhat} = (@var{x}-@var{mu}(1))/@var{mu}(2). 64 ##
63 ## Where @var{mu}(1) = mean (@var{x}), and @var{mu}(2) = std (@var{x}). 65 ## @code{@var{xhat} = (@var{x} - @var{mu}(1)) / @var{mu}(2)} @*
64 ## This linear transformation of @var{x} improves the numerical 66 ## where @var{mu}(1) = mean (@var{x}), and @var{mu}(2) = std (@var{x}).
65 ## stability of the fit. 67 ##
68 ## This linear transformation of @var{x} improves the numerical stability of
69 ## the fit.
66 ## @seealso{polyval, polyaffine, roots, vander, zscore} 70 ## @seealso{polyval, polyaffine, roots, vander, zscore}
67 ## @end deftypefn 71 ## @end deftypefn
68 72
69 ## Author: KH <Kurt.Hornik@wu-wien.ac.at> 73 ## Author: KH <Kurt.Hornik@wu-wien.ac.at>
70 ## Created: 13 December 1994 74 ## Created: 13 December 1994