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ols.m
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1996-09-28
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# Copyright (C) 1994, 1995 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, 675 Mass Ave, Cambridge, MA 02139, USA.
function [BETA, SIGMA, R] = ols (Y, X)
# usage: [BETA, SIGMA [, R]] = ols (Y, X)
#
# Ordinary Least Squares (OLS) estimation for the multivariate model
#
# Y = X*B + E, mean(E) = 0, cov(vec(E)) = kron(S,I)
#
# with Y ... T x p As usual, each row of Y and X is an observation
# X ... T x k and each column a variable.
# B ... k x p
# E ... T x p.
#
# BETA is the OLS estimator for B, i.e.
#
# BETA = pinv(X)*Y,
#
# where pinv(X) denotes the pseudoinverse of X.
# SIGMA is the OLS estimator for the matrix S, i.e.
#
# SIGMA = (Y - X*BETA)'*(Y - X*BETA) / (T - rank(X)).
#
# R = Y - X*BETA is the matrix of OLS residuals.
# Written by Teresa Twaroch (twaroch@ci.tuwien.ac.at) May 1993.
# Dept of Probability Theory and Statistics TU Wien, Austria.
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