-/*
- lib/linreg/linreg.c
-
- Copyright (C) 2005 Free Software Foundation, Inc. Written by Jason H. Stover.
+/* PSPP - a program for statistical analysis.
+ Copyright (C) 2005 Free Software Foundation, Inc. Written by Jason H. Stover.
- 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 of the License, or (at your option)
- any later version.
+ 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 3 of the License, 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.
+ 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 program; if not, write to the Free Software Foundation, Inc., 51
- Franklin Street, Fifth Floor, Boston, MA 02111-1307, USA.
- */
+ You should have received a copy of the GNU General Public License
+ along with this program. If not, see <http://www.gnu.org/licenses/>. */
#include <config.h>
#include <gsl/gsl_fit.h>
/*
Start at c->coeff[1] to avoid the intercept.
*/
- v[result] = pspp_coeff_get_var (c->coeff[1], 0);
+ v[result] = pspp_coeff_get_var (c->coeff[1], 0);
result = (v[result] == NULL) ? 0 : 1;
for (coef = c->coeff[2]; coef < c->coeff[c->n_coeffs]; coef++)
gsl_vector_free (c->indep_std);
gsl_vector_free (c->ss_indeps);
gsl_matrix_free (c->cov);
+ gsl_vector_free (c->ssx);
for (i = 0; i < c->n_coeffs; i++)
{
pspp_coeff_free (c->coeff[i]);
}
gsl_matrix_free (sw);
}
+ else if (cache->method == PSPP_LINREG_CONDITIONAL_INVERSE)
+ {
+ /*
+ Use the SVD of X^T X to find a conditional inverse of X^TX. If
+ the SVD is X^T X = U D V^T, then set the conditional inverse
+ to (X^T X)^c = V D^- U^T. D^- is defined as follows: If entry
+ (i, i) has value sigma_i, then entry (i, i) of D^- is 1 /
+ sigma_i if sigma_i > 0, and 0 otherwise. Then solve the normal
+ equations by setting the estimated parameter vector to
+ (X^TX)^c X^T Y.
+ */
+ }
else
{
gsl_multifit_linear_workspace *wk;