X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Fmath%2Flinreg%2Flinreg.c;h=3c086a98f22ce1868ac581e1cdc4bc359671483f;hb=c17ea35a73b7a690a54c5c6a213de19f0376e74f;hp=c717e4ada4bd690ea7b0938f6c1289525cb24542;hpb=945fd370f9fb880b310fb88f868ad47c2ae84533;p=pspp-builds.git
diff --git a/src/math/linreg/linreg.c b/src/math/linreg/linreg.c
index c717e4ad..3c086a98 100644
--- a/src/math/linreg/linreg.c
+++ b/src/math/linreg/linreg.c
@@ -1,23 +1,20 @@
-/*
- lib/linreg/linreg.c
-
- 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 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.
- */
+/* 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 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.
+
+ You should have received a copy of the GNU General Public License
+ along with this program. If not, see . */
+
+#include
#include
#include
@@ -94,7 +91,7 @@ linreg_mean_std (gsl_vector_const_view v, double *mp, double *sp, double *ssp)
The return value is the number of distinct variables found.
*/
int
-pspp_linreg_get_vars (const void *c_, struct variable **v)
+pspp_linreg_get_vars (const void *c_, const struct variable **v)
{
const pspp_linreg_cache *c = c_;
struct pspp_coeff *coef = NULL;
@@ -113,7 +110,7 @@ pspp_linreg_get_vars (const void *c_, struct variable **v)
/*
Start at c->coeff[1] to avoid the intercept.
*/
- v[result] = (struct variable *) 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++)
@@ -123,13 +120,13 @@ pspp_linreg_get_vars (const void *c_, struct variable **v)
/* Repeated variables are likely to bunch together, at the end
of the array. */
i = result - 1;
- while (i >= 0 && (v[i]->index != tmp->index))
+ while (i >= 0 && v[i] != tmp)
{
i--;
}
if (i < 0 && result < c->n_coeffs)
{
- v[result] = (struct variable *) tmp;
+ v[result] = tmp;
result++;
}
}
@@ -151,10 +148,10 @@ pspp_linreg_cache_alloc (size_t n, size_t p)
c->indep_means = gsl_vector_alloc (p);
c->indep_std = gsl_vector_alloc (p);
c->ssx = gsl_vector_alloc (p); /* Sums of squares for the
- independent variables.
+ independent variables.
*/
c->ss_indeps = gsl_vector_alloc (p); /* Sums of squares for the
- model parameters.
+ model parameters.
*/
c->cov = gsl_matrix_alloc (p + 1, p + 1); /* Covariance matrix. */
c->n_obs = n;
@@ -181,15 +178,18 @@ pspp_linreg_cache_free (void *m)
int i;
pspp_linreg_cache *c = m;
- gsl_vector_free (c->indep_means);
- gsl_vector_free (c->indep_std);
- gsl_vector_free (c->ss_indeps);
- gsl_matrix_free (c->cov);
- for (i = 0; i < c->n_coeffs; i++)
+ if (c != NULL)
{
- pspp_coeff_free (c->coeff[i]);
+ gsl_vector_free (c->indep_means);
+ gsl_vector_free (c->indep_std);
+ gsl_vector_free (c->ss_indeps);
+ gsl_matrix_free (c->cov);
+ for (i = 0; i < c->n_coeffs; i++)
+ {
+ pspp_coeff_free (c->coeff[i]);
+ }
+ free (c);
}
- free (c);
return true;
}
@@ -245,7 +245,7 @@ pspp_linreg (const gsl_vector * Y, const gsl_matrix * X,
cache->dfm = cache->n_indeps;
cache->dfe = cache->dft - cache->dfm;
cache->n_coeffs = X->size2 + 1; /* Adjust this later to allow for
- regression through the origin.
+ regression through the origin.
*/
if (cache->method == PSPP_LINREG_SWEEP)
{
@@ -366,6 +366,18 @@ pspp_linreg (const gsl_vector * Y, const gsl_matrix * X,
}
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;