Mercurial > hg > octave-lyh
view scripts/statistics/base/ols.m @ 14342:2cd56a5e3a66 stable
new tests
* ols.m: New tests.
author | John W. Eaton <jwe@octave.org> |
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date | Tue, 07 Feb 2012 11:41:33 -0500 |
parents | 71efccec5936 |
children | f3d52523cde1 |
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## Copyright (C) 1996-2012 John W. Eaton ## ## 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{beta}, @var{sigma}, @var{r}] =} ols (@var{y}, @var{x}) ## Ordinary least squares estimation for the multivariate model ## @tex ## $y = x b + e$ ## with ## $\bar{e} = 0$, and cov(vec($e$)) = kron ($s, I$) ## @end tex ## @ifnottex ## @w{@math{y = x*b + e}} with ## @math{mean (e) = 0} and @math{cov (vec (e)) = kron (s, I)}. ## @end ifnottex ## where ## @tex ## $y$ is a $t \times p$ matrix, $x$ is a $t \times k$ matrix, ## $b$ is a $k \times p$ matrix, and $e$ is a $t \times p$ matrix. ## @end tex ## @ifnottex ## @math{y} is a @math{t} by @math{p} matrix, @math{x} is a @math{t} by ## @math{k} matrix, @math{b} is a @math{k} by @math{p} matrix, and ## @math{e} is a @math{t} by @math{p} matrix. ## @end ifnottex ## ## Each row of @var{y} and @var{x} is an observation and each column a ## variable. ## ## The return values @var{beta}, @var{sigma}, and @var{r} are defined as ## follows. ## ## @table @var ## @item beta ## The OLS estimator for @math{b}. ## @tex ## $beta$ is calculated directly via $(x^Tx)^{-1} x^T y$ if the matrix $x^Tx$ is ## of full rank. ## @end tex ## @ifnottex ## @var{beta} is calculated directly via @code{inv (x'*x) * x' * y} if the ## matrix @code{x'*x} is of full rank. ## @end ifnottex ## Otherwise, @code{@var{beta} = pinv (@var{x}) * @var{y}} where ## @code{pinv (@var{x})} denotes the pseudoinverse of @var{x}. ## ## @item sigma ## The OLS estimator for the matrix @var{s}, ## ## @example ## @group ## @var{sigma} = (@var{y}-@var{x}*@var{beta})' ## * (@var{y}-@var{x}*@var{beta}) ## / (@var{t}-rank(@var{x})) ## @end group ## @end example ## ## @item r ## The matrix of OLS residuals, @code{@var{r} = @var{y} - @var{x}*@var{beta}}. ## @end table ## @seealso{gls, pinv} ## @end deftypefn ## Author: Teresa Twaroch <twaroch@ci.tuwien.ac.at> ## Created: May 1993 ## Adapted-By: jwe function [beta, sigma, r] = ols (y, x) if (nargin != 2) print_usage (); endif if (! (isnumeric (x) && isnumeric (y))) error ("ols: X and Y must be numeric matrices or vectors"); endif if (ndims (x) != 2 || ndims (y) != 2) error ("ols: X and Y must be 2-D matrices or vectors"); endif [nr, nc] = size (x); [ry, cy] = size (y); if (nr != ry) error ("ols: number of rows of X and Y must be equal"); endif if (isinteger (x)) x = double (x); endif if (isinteger (y)) y = double (y); endif ## Start of algorithm z = x' * x; [u, p] = chol (z); if (p) beta = pinv (x) * y; else beta = u \ (u' \ (x' * y)); endif if (isargout (2) || isargout (3)) r = y - x * beta; endif if (isargout (2)) ## z is of full rank, avoid the SVD in rnk if (p == 0) rnk = columns (z); else rnk = rank (z); endif sigma = r' * r / (nr - rnk); endif endfunction %!test %! x = [1:5]'; %! y = 3*x + 2; %! x = [x, ones(5,1)]; %! assert (ols(y,x), [3; 2], 50*eps) %!test %! x = [1, 2; 3, 4]; %! y = [1; 2]; %! [b, s, r] = ols (x, y); %! assert (b, [1.4, 2], 2*eps); %! assert (s, [0.2, 0; 0, 0], 2*eps); %! assert (r, [-0.4, 0; 0.2, 0], 2*eps); %!test %! x = [1, 2; 3, 4]; %! y = [1; 2]; %! [b, s] = ols (x, y); %! assert (b, [1.4, 2], 2*eps); %! assert (s, [0.2, 0; 0, 0], 2*eps); %!test %! x = [1, 2; 3, 4]; %! y = [1; 2]; %! b = ols (x, y); %! assert (b, [1.4, 2], 2*eps); %% Test input validation %!error ols (); %!error ols (1); %!error ols (1, 2, 3); %!error ols ([true, true], [1, 2]); %!error ols ([1, 2], [true, true]); %!error ols (ones (2,2,2), ones (2,2)); %!error ols (ones (2,2), ones (2,2,2)); %!error ols (ones(1,2), ones(2,2));