Mercurial > hg > octave-lyh
view scripts/statistics/tests/f_test_regression.m @ 5428:2a16423e4aa0
[project @ 2005-08-23 18:38:27 by jwe]
author | jwe |
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date | Tue, 23 Aug 2005 18:38:28 +0000 |
parents | 4c8a2e4e0717 |
children | 34f96dd5441b |
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## Copyright (C) 1995, 1996, 1997 Kurt Hornik ## ## This file is part of Octave. ## ## Octave 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 2, or (at your option) ## any later version. ## ## Octave 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 Octave; see the file COPYING. If not, write to the Free ## Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA ## 02110-1301, USA. ## -*- texinfo -*- ## @deftypefn {Function File} {[@var{pval}, @var{f}, @var{df_num}, @var{df_den}] =} f_test_regression (@var{y}, @var{x}, @var{rr}, @var{r}) ## Perform an F test for the null hypothesis rr * b = r in a classical ## normal regression model y = X * b + e. ## ## Under the null, the test statistic @var{f} follows an F distribution ## with @var{df_num} and @var{df_den} degrees of freedom. ## ## The p-value (1 minus the CDF of this distribution at @var{f}) is ## returned in @var{pval}. ## ## If not given explicitly, @var{r} = 0. ## ## If no output argument is given, the p-value is displayed. ## @end deftypefn ## Author: KH <Kurt.Hornik@wu-wien.ac.at> ## Description: Test linear hypotheses in linear regression model function [pval, f, df_num, df_den] = f_test_regression (y, X, R, r) if (nargin < 3 || nargin > 4) usage ("[pval, f, df_num, df_den] = f_test_regression (y, X, R, r)"); endif [T, k] = size (X); if (! (isvector (y) && (length (y) == T))) error ("f_test_regression: y must be a vector of length rows (X)"); endif y = reshape (y, T, 1); [q, c_R ] = size (R); if (c_R != k) error ("f_test_regression: R must have as many columns as X"); endif if (nargin == 4) s_r = size (r); if ((min (s_r) != 1) || (max (s_r) != q)) error ("f_test_regression: r must be a vector of length rows (R)"); endif r = reshape (r, q, 1); else r = zeros (q, 1); endif df_num = q; df_den = T - k; [b, v] = ols (y, X); diff = R * b - r; f = diff' * inv (R * inv (X' * X) * R') * diff / (q * v); pval = 1 - f_cdf (f, df_num, df_den); if (nargout == 0) printf (" pval: %g\n", pval); endif endfunction