#include <stdlib.h>
#include <data/case.h>
-#include <data/category.h>
#include <data/casegrouper.h>
#include <data/casereader.h>
#include <data/dictionary.h>
#include <language/data-io/file-handle.h>
#include <language/lexer/lexer.h>
#include <libpspp/compiler.h>
-#include <libpspp/hash.h>
#include <libpspp/message.h>
-#include <math/covariance-matrix.h>
-#include <math/coefficient.h>
+#include <math/covariance.h>
+#include <math/categoricals.h>
#include <math/linreg.h>
#include <math/moments.h>
-#include <output/table.h>
+#include <output/tab.h>
#include "xalloc.h"
#include "gettext.h"
struct cmd_glm *cmd UNUSED, void *aux UNUSED)
{
const struct dictionary *dict = dataset_dict (ds);
+ size_t i;
if ((lex_token (lexer) != T_ID
|| dict_lookup_var (dict, lex_tokid (lexer)) == NULL)
&& lex_token (lexer) != T_ALL)
return 2;
- if (!parse_variables_const
- (lexer, dict, &v_dependent, &n_dependent, PV_NONE))
+ if (!parse_variables_const (lexer, dict, &v_dependent, &n_dependent, PV_NONE))
{
free (v_dependent);
return 0;
}
+ for (i = 0; i < n_dependent; i++)
+ {
+ assert (var_is_numeric (v_dependent[i]));
+ }
assert (n_dependent);
if (n_dependent > 1)
msg (SE, _("Multivariate GLM not yet supported"));
return 1;
}
-/*
- COV is the covariance matrix for variables included in the
- model. That means the dependent variable is in there, too.
- */
-static void
-coeff_init (pspp_linreg_cache * c, const struct design_matrix *cov)
-{
- c->coeff = xnmalloc (cov->m->size2, sizeof (*c->coeff));
- c->n_coeffs = cov->m->size2 - 1;
- pspp_coeff_init (c->coeff, cov);
-}
-
-
-static pspp_linreg_cache *
-fit_model (const struct covariance_matrix *cov,
+static linreg *
+fit_model (const struct covariance *cov,
const struct variable *dep_var,
const struct variable ** indep_vars,
size_t n_data, size_t n_indep)
{
- pspp_linreg_cache *result = NULL;
- result = pspp_linreg_cache_alloc (dep_var, indep_vars, n_data, n_indep);
- coeff_init (result, covariance_to_design (cov));
- pspp_linreg_with_cov (cov, result);
+ linreg *result = NULL;
return result;
}
const struct dataset *ds)
{
casenumber row;
- const struct variable **indep_vars;
- const struct variable **all_vars;
+ const struct variable **numerics = NULL;
+ const struct variable **categoricals = NULL;
int n_indep = 0;
- pspp_linreg_cache *model = NULL;
+ linreg *model = NULL;
pspp_linreg_opts lopts;
struct ccase *c;
size_t i;
- size_t n_all_vars;
size_t n_data; /* Number of valid cases. */
+ size_t n_categoricals = 0;
+ size_t n_numerics;
struct casereader *reader;
- struct covariance_matrix *cov;
+ struct covariance *cov;
c = casereader_peek (input, 0);
if (c == NULL)
lopts.get_depvar_mean_std = 1;
lopts.get_indep_mean_std = xnmalloc (n_dependent, sizeof (int));
- indep_vars = xnmalloc (cmd->n_by, sizeof *indep_vars);
- n_all_vars = cmd->n_by + n_dependent;
- all_vars = xnmalloc (n_all_vars, sizeof *all_vars);
- for (i = 0; i < n_dependent; i++)
+
+ n_numerics = n_dependent;
+ for (i = 0; i < cmd->n_with; i++)
{
- all_vars[i] = v_dependent[i];
+ if (var_is_alpha (cmd->v_with[i]))
+ {
+ n_categoricals++;
+ }
+ else
+ {
+ n_numerics++;
+ }
}
for (i = 0; i < cmd->n_by; i++)
{
- indep_vars[i] = cmd->v_by[i];
- all_vars[i + n_dependent] = cmd->v_by[i];
+ if (var_is_alpha (cmd->v_by[i]))
+ {
+ n_categoricals++;
+ }
+ else
+ {
+ n_numerics++;
+ }
}
- n_indep = cmd->n_by;
+ numerics = xnmalloc (n_numerics, sizeof *numerics);
+ categoricals = xnmalloc (n_categoricals, sizeof (*categoricals));
+ size_t j = 0;
+ size_t k = 0;
+ for (i = 0; i < cmd->n_by; i++)
+ {
+ if (var_is_alpha (cmd->v_by[i]))
+ {
+ categoricals[j] = cmd->v_by[i];
+ j++;
+ }
+ else
+ {
+ numerics[k] = cmd->v_by[i];
+ k++;
+ }
+ }
+ for (i = 0; i < cmd->n_with; i++)
+ {
+ if (var_is_alpha (cmd->v_with[i]))
+ {
+ categoricals[j] = cmd->v_with[i];
+ j++;
+ }
+ else
+ {
+ numerics[k] = cmd->v_with[i];
+ k++;
+ }
+ }
+ for (i = 0; i < n_dependent; i++)
+ {
+ numerics[k] = v_dependent[i];
+ k++;
+ }
+
+ struct categoricals *cats =
+ categoricals_create (categoricals, n_categoricals,
+ NULL, MV_NEVER,
+ NULL, NULL, NULL, NULL);
+
+ cov = covariance_2pass_create (n_numerics, numerics,
+ cats,
+ NULL, MV_NEVER);
reader = casereader_clone (input);
- reader = casereader_create_filter_missing (reader, indep_vars, n_indep,
+ reader = casereader_create_filter_missing (reader, numerics, n_numerics,
MV_ANY, NULL, NULL);
- reader = casereader_create_filter_missing (reader, v_dependent, 1,
+ reader = casereader_create_filter_missing (reader, categoricals, n_categoricals,
MV_ANY, NULL, NULL);
+ struct casereader *r = casereader_clone (reader);
- if (n_indep > 0)
+ reader = casereader_create_counter (reader, &row, -1);
+
+ for (; (c = casereader_read (reader)) != NULL; case_unref (c))
{
- for (i = 0; i < n_all_vars; i++)
- if (var_is_alpha (all_vars[i]))
- cat_stored_values_create (all_vars[i]);
-
- reader = casereader_create_counter (reader, &row, -1);
-
- for (i = 0; i < n_inter; i++)
- for (; (c = casereader_read (reader)) != NULL; case_unref (c))
- {
- /*
- Accumulate the covariance matrix.
- */
- n_data++;
- }
- casereader_destroy (reader);
+ covariance_accumulate_pass1 (cov, c);
}
- else
+ for (; (c = casereader_read (r)) != NULL; case_unref (c))
{
- msg (SE, gettext ("No valid data found. This command was skipped."));
+ covariance_accumulate_pass2 (cov, c);
}
- free (indep_vars);
+
+ covariance_destroy (cov);
+ casereader_destroy (reader);
+ casereader_destroy (r);
+
+ free (numerics);
+ free (categoricals);
free (lopts.get_indep_mean_std);
casereader_destroy (input);