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- ## Copyright (C) 1996, 1997 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 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, 59 Temple Place - Suite 330, Boston, MA
- ## 02111-1307, USA.
-
- ## -*- texinfo -*-
- ## @deftypefn {Function File} {[@var{beta}, @var{sigma}, @var{r}] =} ols (@var{y}, @var{x})
- ## Ordinary least squares estimation for the multivariate model
- ## @iftex
- ## @tex
- ## $y = x b + e$
- ## with
- ## $\bar{e} = 0$, and cov(vec($e$)) = kron ($s, I$)
- ## @end tex
- ## @end iftex
- ## @ifinfo
- ## @code{@var{y} = @var{x}*@var{b} + @var{e}} with
- ## @code{mean (@var{e}) = 0} and @code{cov (vec (@var{e})) = kron (@var{s},
- ## @var{I})}.
- ## @end ifinfo
- ## where
- ## @iftex
- ## @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
- ## @end iftex
- ## @ifinfo
- ## @var{y} is a @var{t} by @var{p} matrix, @var{X} is a @var{t} by @var{k}
- ## matrix, @var{B} is a @var{k} by @var{p} matrix, and @var{e} is a @var{t}
- ## by @var{p} matrix.
- ## @end ifinfo
- ##
- ## 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 @var{b}, @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
- ## @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)
- error("usage : [BETA, SIGMA [, R]] = ols (Y, X)");
- endif
-
- [nr, nc] = size (X);
- [ry, cy] = size (Y);
- if (nr != ry)
- error ("ols: incorrect matrix dimensions");
- endif
-
- Z = X' * X;
- r = rank (Z);
-
- if (r == nc)
- BETA = inv (Z) * X' * Y;
- else
- BETA = pinv (X) * Y;
- endif
-
- R = Y - X * BETA;
- SIGMA = R' * R / (nr - r);
-
- endfunction
-