/* PSPP - a program for statistical analysis.
- Copyright (C) 2005, 2009 Free Software Foundation, Inc.
+ Copyright (C) 2005, 2009, 2010, 2011 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
#include <gsl/gsl_vector.h>
#include <math.h>
#include <stdlib.h>
-#include <data/case.h>
-#include <data/casegrouper.h>
-#include <data/casereader.h>
-#include <data/dictionary.h>
-#include <data/missing-values.h>
-#include <data/procedure.h>
-#include <data/transformations.h>
-#include <data/value-labels.h>
-#include <data/variable.h>
-#include <language/command.h>
-#include <language/dictionary/split-file.h>
-#include <language/data-io/file-handle.h>
-#include <language/lexer/lexer.h>
-#include <libpspp/compiler.h>
-#include <libpspp/message.h>
-#include <libpspp/taint.h>
-#include <math/covariance.h>
-#include <math/linreg.h>
-#include <math/moments.h>
-#include <output/tab.h>
-
-#include "xalloc.h"
+
+#include "data/case.h"
+#include "data/casegrouper.h"
+#include "data/casereader.h"
+#include "data/dictionary.h"
+#include "data/missing-values.h"
+#include "data/procedure.h"
+#include "data/transformations.h"
+#include "data/value-labels.h"
+#include "data/variable.h"
+#include "language/command.h"
+#include "language/data-io/file-handle.h"
+#include "language/dictionary/split-file.h"
+#include "language/lexer/lexer.h"
+#include "libpspp/compiler.h"
+#include "libpspp/message.h"
+#include "libpspp/taint.h"
+#include "math/covariance.h"
+#include "math/linreg.h"
+#include "math/moments.h"
+#include "output/tab.h"
+
+#include "gl/intprops.h"
+#include "gl/xalloc.h"
#include "gettext.h"
#define _(msgid) gettext (msgid)
tab_double (t, 4, 1, 0, 0.0, NULL);
t_stat = linreg_intercept (c) / std_err;
tab_double (t, 5, 1, 0, t_stat, NULL);
- pval = 2 * gsl_cdf_tdist_Q (fabs (t_stat), 1.0);
+ pval = 2 * gsl_cdf_tdist_Q (fabs (t_stat), (double) (linreg_n_obs (c) - linreg_n_coeffs (c)));
tab_double (t, 6, 1, 0, pval, NULL);
for (j = 0; j < linreg_n_coeffs (c); j++)
{
return TRNS_CONTINUE;
}
-/*
- Returns false if NAME is a duplicate of any existing variable name.
-*/
-static bool
-try_name (const struct dictionary *dict, const char *name)
+static char *
+reg_get_name (const struct dictionary *dict, const char *prefix)
{
- if (dict_lookup_var (dict, name) != NULL)
- return false;
-
- return true;
-}
-
-static void
-reg_get_name (const struct dictionary *dict, char name[VAR_NAME_LEN],
- const char prefix[VAR_NAME_LEN])
-{
- int i = 1;
+ char *name;
+ int i;
- snprintf (name, VAR_NAME_LEN, "%s%d", prefix, i);
- while (!try_name (dict, name))
+ /* XXX handle too-long prefixes */
+ name = xmalloc (strlen (prefix) + INT_BUFSIZE_BOUND (i) + 1);
+ for (i = 1; ; i++)
{
- i++;
- snprintf (name, VAR_NAME_LEN, "%s%d", prefix, i);
+ sprintf (name, "%s%d", prefix, i);
+ if (dict_lookup_var (dict, name) == NULL)
+ return name;
}
}
{
struct dictionary *dict = dataset_dict (ds);
static int trns_index = 1;
- char name[VAR_NAME_LEN];
+ char *name;
struct variable *new_var;
struct reg_trns *t = NULL;
t->trns_id = trns_index;
t->n_trns = n_trns;
t->c = c;
- reg_get_name (dict, name, prefix);
- new_var = dict_create_var (dict, name, 0);
- assert (new_var != NULL);
+
+ name = reg_get_name (dict, prefix);
+ new_var = dict_create_var_assert (dict, name, 0);
+ free (name);
+
*v = new_var;
add_transformation (ds, f, regression_trns_free, t);
trns_index++;
{
const struct dictionary *dict = dataset_dict (ds);
- lex_match (lexer, '=');
+ lex_match (lexer, T_EQUALS);
if ((lex_token (lexer) != T_ID
- || dict_lookup_var (dict, lex_tokid (lexer)) == NULL)
+ || dict_lookup_var (dict, lex_tokcstr (lexer)) == NULL)
&& lex_token (lexer) != T_ALL)
return 2;
size_t dep_subscript;
size_t *rows;
const gsl_matrix *ssizes;
- const gsl_matrix *cm;
+ gsl_matrix *cm;
const gsl_matrix *mean_matrix;
const gsl_matrix *ssize_matrix;
double result = 0.0;
gsl_matrix_set (cov, cov->size1 - 1, cov->size1 - 1,
gsl_matrix_get (cm, dep_subscript, dep_subscript));
free (rows);
+ gsl_matrix_free (cm);
return result;
}
+static size_t
+get_n_all_vars (struct cmd_regression *cmd)
+{
+ size_t result = n_variables;
+ size_t i;
+ size_t j;
+ result += cmd->n_dependent;
+ for (i = 0; i < cmd->n_dependent; i++)
+ {
+ for (j = 0; j < n_variables; j++)
+ {
+ if (v_variables[j] == cmd->v_dependent[i])
+ {
+ result--;
+ }
+ }
+ }
+ return result;
+}
+static void
+fill_all_vars (const struct variable **vars, struct cmd_regression *cmd)
+{
+ size_t i;
+ size_t j;
+ bool absent;
+
+ for (i = 0; i < n_variables; i++)
+ {
+ vars[i] = v_variables[i];
+ }
+ for (i = 0; i < cmd->n_dependent; i++)
+ {
+ absent = true;
+ for (j = 0; j < n_variables; j++)
+ {
+ if (cmd->v_dependent[i] == v_variables[j])
+ {
+ absent = false;
+ break;
+ }
+ }
+ if (absent)
+ {
+ vars[i + n_variables] = cmd->v_dependent[i];
+ }
+ }
+}
static bool
run_regression (struct casereader *input, struct cmd_regression *cmd,
struct dataset *ds, linreg **models)
struct ccase *c;
struct covariance *cov;
const struct variable **vars;
+ const struct variable **all_vars;
const struct variable *dep_var;
struct casereader *reader;
const struct dictionary *dict;
- gsl_matrix *this_cm;
+ size_t n_all_vars;
assert (models != NULL);
{
dict_get_vars (dict, &v_variables, &n_variables, 0);
}
+ n_all_vars = get_n_all_vars (cmd);
+ all_vars = xnmalloc (n_all_vars, sizeof (*all_vars));
+ fill_all_vars (all_vars, cmd);
vars = xnmalloc (n_variables, sizeof (*vars));
- means = xnmalloc (n_variables, sizeof (*means));
- cov = covariance_1pass_create (n_variables, v_variables,
+ means = xnmalloc (n_all_vars, sizeof (*means));
+ cov = covariance_1pass_create (n_all_vars, all_vars,
dict_get_weight (dict), MV_ANY);
reader = casereader_clone (input);
for (k = 0; k < cmd->n_dependent; k++)
{
+ gsl_matrix *this_cm;
dep_var = cmd->v_dependent[k];
n_indep = identify_indep_vars (vars, dep_var);
this_cm = gsl_matrix_alloc (n_indep + 1, n_indep + 1);
n_data = fill_covariance (this_cm, cov, vars, n_indep,
- dep_var, v_variables, n_variables, means);
+ dep_var, all_vars, n_all_vars, means);
models[k] = linreg_alloc (dep_var, (const struct variable **) vars,
n_data, n_indep);
models[k]->depvar = dep_var;
linreg_free (models[k]);
models[k] = NULL;
}
+ gsl_matrix_free (this_cm);
}
casereader_destroy (reader);
free (vars);
+ free (all_vars);
free (means);
casereader_destroy (input);
covariance_destroy (cov);
projects / pspp-builds.git / blobdiff