Mercurial > hg > octave-nkf
view scripts/statistics/tests/t_test_regression.m @ 20818:9d2023d1a63c
binoinv.m: Implement binary search algorithm for 28X performance increase (bug #34363).
* binoinv.m: Call new functions scalar_binoinv or vector_binoinv to calculate
binoinv. If there are still uncalculated values then call bin_search_binoinv
to perform binary search for remaining values. Add more BIST tests.
* binoinv.m (scalar_binoinv): New subfunction to calculate binoinv for scalar x.
Stops when x > 1000.
* binoinv.m (vector_binoinv): New subfunction to calculate binoinv for scalar x.
Stops when x > 1000.
author | Lachlan Andrew <lachlanbis@gmail.com> |
---|---|
date | Sun, 11 Oct 2015 19:49:40 -0700 |
parents | aa36fb998a4d |
children |
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## Copyright (C) 1995-2015 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 3 of the License, 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, see ## <http://www.gnu.org/licenses/>. ## -*- texinfo -*- ## @deftypefn {Function File} {[@var{pval}, @var{t}, @var{df}] =} t_test_regression (@var{y}, @var{x}, @var{rr}, @var{r}, @var{alt}) ## Perform a t test for the null hypothesis ## @nospell{@code{@var{rr} * @var{b} = @var{r}}} in a classical normal ## regression model @code{@var{y} = @var{x} * @var{b} + @var{e}}. ## ## Under the null, the test statistic @var{t} follows a @var{t} distribution ## with @var{df} degrees of freedom. ## ## If @var{r} is omitted, a value of 0 is assumed. ## ## With the optional argument string @var{alt}, the alternative of interest ## can be selected. If @var{alt} is @qcode{"!="} or @qcode{"<>"}, the null ## is tested against the two-sided alternative @nospell{@code{@var{rr} * ## @var{b} != @var{r}}}. If @var{alt} is @qcode{">"}, the one-sided ## alternative @nospell{@code{@var{rr} * @var{b} > @var{r}}} is used. ## Similarly for @var{"<"}, the one-sided alternative @nospell{@code{@var{rr} ## * @var{b} < @var{r}}} is used. The default is the two-sided case. ## ## The p-value of the test is returned in @var{pval}. ## ## If no output argument is given, the p-value of the test is displayed. ## @end deftypefn ## Author: KH <Kurt.Hornik@wu-wien.ac.at> ## Description: Test one linear hypothesis in linear regression model function [pval, t, df] = t_test_regression (y, x, rr, r, alt) if (nargin == 3) r = 0; alt = "!="; elseif (nargin == 4) if (ischar (r)) alt = r; r = 0; else alt = "!="; endif elseif (! (nargin == 5)) print_usage (); endif if (! isscalar (r)) error ("t_test_regression: R must be a scalar"); elseif (! ischar (alt)) error ("t_test_regression: ALT must be a string"); endif [T, k] = size (x); if (! (isvector (y) && (length (y) == T))) error ("t_test_regression: Y must be a vector of length rows (X)"); endif s = size (rr); if (! ((max (s) == k) && (min (s) == 1))) error ("t_test_regression: RR must be a vector of length columns (X)"); endif rr = reshape (rr, 1, k); y = reshape (y, T, 1); [b, v] = ols (y, x); df = T - k; t = (rr * b - r) / sqrt (v * rr * inv (x' * x) * rr'); cdf = tcdf (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