#include <math/coefficient.h>
#include <math/linreg.h>
#include <math/coefficient.h>
+#include <math/design-matrix.h>
+#include <src/data/category.h>
#include <src/data/variable.h>
#include <src/data/value.h>
#include <gl/xalloc.h>
values as indicated by opts.
*/
int
-pspp_linreg (const gsl_vector * Y, const gsl_matrix * X,
+pspp_linreg (const gsl_vector * Y, const struct design_matrix *dm,
const pspp_linreg_opts * opts, pspp_linreg_cache * cache)
{
int rc;
gsl_matrix *design = NULL;
gsl_matrix_view xtx;
- gsl_matrix_view xm;
+ gsl_matrix *xm;
gsl_matrix_view xmxtx;
gsl_vector_view xty;
gsl_vector_view xi;
gsl_vector_view xj;
gsl_vector *param_estimates;
+ struct pspp_coeff *coef;
+ const struct variable *v;
+ const union value *val;
size_t i;
size_t j;
cache->depvar_std = s;
cache->sst = ss;
}
- for (i = 0; i < cache->n_indeps; i++)
+
+ cache->dft = cache->n_obs - 1;
+ cache->dfm = cache->n_indeps;
+ cache->dfe = cache->dft - cache->dfm;
+ cache->n_coeffs = dm->m->size2;
+ cache->intercept = 0.0;
+
+ for (i = 0; i < dm->m->size2; i++)
{
if (opts->get_indep_mean_std[i])
{
- linreg_mean_std (gsl_matrix_const_column (X, i), &m, &s, &ss);
- gsl_vector_set (cache->indep_means, i, m);
- gsl_vector_set (cache->indep_std, i, s);
+ linreg_mean_std (gsl_matrix_const_column (dm->m, i), &m, &s, &ss);
+ v = design_matrix_col_to_var (dm, i);
+ val = NULL;
+ if (var_is_alpha (v))
+ {
+ j = i - design_matrix_var_to_column (dm, v);
+ val = cat_subscript_to_value (j, v);
+ }
+ coef = pspp_linreg_get_coeff (cache, v, val);
+ pspp_coeff_set_mean (coef, m);
+ pspp_coeff_set_sd (coef, s);
gsl_vector_set (cache->ssx, i, ss);
+
}
}
- cache->dft = cache->n_obs - 1;
- cache->dfm = cache->n_indeps;
- cache->dfe = cache->dft - cache->dfm;
- cache->n_coeffs = X->size2;
- cache->intercept = 0.0;
if (cache->method == PSPP_LINREG_SWEEP)
{
gsl_matrix *sw;
/*
Subtract the means to improve the condition of the design
- matrix. This requires copying X and Y. We do not divide by the
+ matrix. This requires copying dm->m and Y. We do not divide by the
standard deviations of the independent variables here since doing
so would cause a miscalculation of the residual sums of
squares. Dividing by the standard deviation is done GSL's linear
(i.e., a column of 1's). If using PSPP_LINREG_QR, we need that column,
so design is allocated here when sweeping, or below if using QR.
*/
- design = gsl_matrix_alloc (X->size1, X->size2);
- for (i = 0; i < X->size2; i++)
+ design = gsl_matrix_alloc (dm->m->size1, dm->m->size2);
+ for (i = 0; i < dm->m->size2; i++)
{
- m = gsl_vector_get (cache->indep_means, i);
- for (j = 0; j < X->size1; j++)
+ v = design_matrix_col_to_var (dm, i);
+ m = pspp_linreg_get_indep_variable_mean (cache, v);
+ for (j = 0; j < dm->m->size1; j++)
{
- tmp = (gsl_matrix_get (X, j, i) - m);
+ tmp = (gsl_matrix_get (dm->m, j, i) - m);
gsl_matrix_set (design, j, i, tmp);
}
}
{
tmp = gsl_matrix_get (sw, i, cache->n_indeps);
cache->coeff[i]->estimate = tmp;
- m -= tmp * gsl_vector_get (cache->indep_means, i);
+ m -= tmp * pspp_linreg_get_indep_variable_mean (cache, design_matrix_col_to_var (dm, i));
}
/*
Get the covariance matrix of the parameter estimates.
*/
xtx = gsl_matrix_submatrix (sw, 0, 0, cache->n_indeps, cache->n_indeps);
xmxtx = gsl_matrix_submatrix (cache->cov, 0, 1, 1, cache->n_indeps);
- xm = gsl_matrix_view_vector (cache->indep_means, 1, cache->n_indeps);
+ xm = gsl_matrix_calloc (1, cache->n_indeps);
+ for (i = 0; i < xm->size2; i++)
+ {
+ gsl_matrix_set (xm, 0, i,
+ pspp_linreg_get_indep_variable_mean (cache, design_matrix_col_to_var (dm, i)));
+ }
rc = gsl_blas_dsymm (CblasRight, CblasUpper, cache->mse,
- &xtx.matrix, &xm.matrix, 0.0, &xmxtx.matrix);
+ &xtx.matrix, xm, 0.0, &xmxtx.matrix);
+ gsl_matrix_free (xm);
if (rc == GSL_SUCCESS)
{
tmp = cache->mse / cache->n_obs;
for (i = 1; i < 1 + cache->n_indeps; i++)
{
tmp -= gsl_matrix_get (cache->cov, 0, i)
- * gsl_vector_get (cache->indep_means, i - 1);
+ * pspp_linreg_get_indep_variable_mean (cache, design_matrix_col_to_var (dm, i - 1));
}
gsl_matrix_set (cache->cov, 0, 0, tmp);
Use QR decomposition via GSL.
*/
- param_estimates = gsl_vector_alloc (1 + X->size2);
- design = gsl_matrix_alloc (X->size1, 1 + X->size2);
+ param_estimates = gsl_vector_alloc (1 + dm->m->size2);
+ design = gsl_matrix_alloc (dm->m->size1, 1 + dm->m->size2);
- for (j = 0; j < X->size1; j++)
+ for (j = 0; j < dm->m->size1; j++)
{
gsl_matrix_set (design, j, 0, 1.0);
- for (i = 0; i < X->size2; i++)
+ for (i = 0; i < dm->m->size2; i++)
{
- tmp = gsl_matrix_get (X, j, i);
+ tmp = gsl_matrix_get (dm->m, j, i);
gsl_matrix_set (design, j, i + 1, tmp);
}
}
pspp_linreg_get_coeff (const pspp_linreg_cache * c,
const struct variable *v, const union value *val)
{
- int i;
- struct pspp_coeff *result = NULL;
- const struct variable *tmp = NULL;
-
if (c == NULL)
{
return NULL;
{
return NULL;
}
- i = 0;
- result = c->coeff[0];
- tmp = pspp_coeff_get_var (result, 0);
- while (tmp != v && i < c->n_coeffs)
+ return pspp_coeff_var_to_coeff (v, c->coeff, c->n_coeffs, val);
+}
+/*
+ Return the standard deviation of the independent variable.
+ */
+double pspp_linreg_get_indep_variable_sd (pspp_linreg_cache *c, const struct variable *v)
+{
+ if (var_is_numeric (v))
{
- result = c->coeff[i];
- tmp = pspp_coeff_get_var (result, 0);
- i++;
+ const struct pspp_coeff *coef;
+ coef = pspp_linreg_get_coeff (c, v, NULL);
+ return pspp_coeff_get_sd (coef);
}
- if (tmp != v)
+ return GSL_NAN;
+}
+
+void pspp_linreg_set_indep_variable_sd (pspp_linreg_cache *c, const struct variable *v,
+ double s)
+{
+ if (var_is_numeric (v))
{
- /*
- Not found.
- */
- return NULL;
+ struct pspp_coeff *coef;
+ coef = pspp_linreg_get_coeff (c, v, NULL);
+ pspp_coeff_set_sd (coef, s);
}
+}
+
+/*
+ Mean of the independent variable.
+ */
+double pspp_linreg_get_indep_variable_mean (pspp_linreg_cache *c, const struct variable *v)
+{
if (var_is_numeric (v))
{
- return result;
+ struct pspp_coeff *coef;
+ coef = pspp_linreg_get_coeff (c, v, NULL);
+ return pspp_coeff_get_mean (coef);
}
- else if (val != NULL)
+ return GSL_NAN;
+}
+
+void pspp_linreg_set_indep_variable_mean (pspp_linreg_cache *c, const struct variable *v,
+ double m)
+{
+ if (var_is_numeric (v))
{
- /*
- If v is categorical, we need to ensure the coefficient
- matches the VAL.
- */
- while (tmp != v && i < c->n_coeffs
- && compare_values (pspp_coeff_get_value (result, tmp),
- val, var_get_width (v)))
- { /* FIX THIS */
- i++;
- result = c->coeff[i];
- tmp = pspp_coeff_get_var (result, 0);
- }
- if (i == c->n_coeffs && tmp != v)
- {
- return NULL;
- }
- return result;
+ struct pspp_coeff *coef;
+ coef = pspp_linreg_get_coeff (c, v, NULL);
+ pspp_coeff_set_mean (coef, m);
}
- return NULL;
}
projects / pspp-builds.git / blobdiff