/* PSPP - a program for statistical analysis.
- Copyright (C) 2005 Free Software Foundation, Inc. Written by Jason H. Stover.
+ Copyright (C) 2005 Free Software Foundation, Inc.
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
pspp_linreg_get_vars (const void *c_, const struct variable **v)
{
const pspp_linreg_cache *c = c_;
- struct pspp_coeff *coef = NULL;
const struct variable *tmp;
int i;
+ int j;
int result = 0;
/*
/*
Start at c->coeff[1] to avoid the intercept.
*/
- 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++)
+ for (j = 1; j < c->n_coeffs; j++)
{
- tmp = pspp_coeff_get_var (coef, 0);
+ tmp = pspp_coeff_get_var (c->coeff[j], 0);
assert (tmp != NULL);
/* Repeated variables are likely to bunch together, at the end
of the array. */
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]);
}
+ free (c->coeff);
free (c);
}
return true;
const pspp_linreg_opts * opts, pspp_linreg_cache * cache)
{
int rc;
- gsl_matrix *design;
+ gsl_matrix *design = NULL;
gsl_matrix_view xtx;
gsl_matrix_view xm;
gsl_matrix_view xmxtx;
}
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;