Mercurial > hg > octave-nkf
view scripts/statistics/tests/t_test_regression.m @ 3273:eb27ea9b7ff8
[project @ 1999-10-12 02:22:25 by jwe]
author | jwe |
---|---|
date | Tue, 12 Oct 1999 02:27:27 +0000 |
parents | 781c930425fd |
children | f8dde1807dee |
line wrap: on
line source
## Copyright (C) 1995, 1996, 1997 Kurt Hornik ## ## 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 2, 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 file. If not, write to the Free Software Foundation, ## 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. ## usage: [pval, t, df] = t_test_regression (y, X, R [, r] [, alt]) ## ## Performs an t test for the null hypothesis R * b = r in a classical ## normal regression model y = X * b + e. ## Under the null, the test statistic t follows a t distribution with ## df degrees of freedom. ## ## r is taken as 0 if not given explicitly. ## ## With the optional argument string alt, the alternative of interest ## can be selected. ## If alt is "!=" or "<>", the null is tested against the two-sided ## alternative R * b != r. ## If alt is ">", the one-sided alternative R * b > r is used, ## similarly for "<". ## The default is the two-sided case. ## ## pval is the p-value of the test. ## ## If no output argument is given, the p-value of the test is displayed. ## Author: KH <Kurt.Hornik@ci.tuwien.ac.at> ## Description: Test one linear hypothesis in linear regression model function [pval, t, df] = t_test_regression (y, X, R, r, alt) if (nargin == 3) r = 0; alt = "!="; elseif (nargin == 4) if (isstr (r)) alt = r; r = 0; else alt = "!="; endif elseif !(nargin == 5) usage (["[pval, t, df] ", ... "= t_test_regression (y, X, R [, r] [, alt]"]); endif if (! is_scalar (r)) error ("t_test_regression: r must be a scalar"); elseif (! isstr (alt)) error ("t_test_regression: alt must be a string"); endif [T, k] = size (X); if !(is_vector (y) && (length (y) == T)) error (["t_test_regression: ", ... "y must be a vector of length rows (X)"]); endif s = size (R); if !((max (s) == k) && (min (s) == 1)) error (["t_test_regression: ", ... "R must be a vector of length columns (X)"]); endif R = reshape (R, 1, k); y = reshape (y, T, 1); [b, v] = ols (y, X); df = T - k; t = (R * b - r) / sqrt (v * R * inv (X' * X) * R'); cdf = t_cdf (t, df); if (strcmp (alt, "!=") || strcmp (alt, "<>")) pval = 2 * min (cdf, 1 - cdf); elseif strcmp (alt, ">") pval = 1 - cdf; elseif strcmp (alt, "<") pval = cdf; else error ("t_test_regression: the value `%s' for alt is not possible", alt); endif if (nargout == 0) printf ("pval: %g\n", pval); endif endfunction