X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Flanguage%2Fstats%2Fregression.q;h=d5008b5681178b5890584ca08b20ee04169a6e31;hb=26791c51431aa1b848b6e3997d2402680513c448;hp=1f2ac2a6bac15051def19c85dc6b7e1af180dcde;hpb=dc78471910e82d59232ce9b137b7c4fc4992d174;p=pspp-builds.git
diff --git a/src/language/stats/regression.q b/src/language/stats/regression.q
index 1f2ac2a6..d5008b56 100644
--- a/src/language/stats/regression.q
+++ b/src/language/stats/regression.q
@@ -1,20 +1,18 @@
-/* PSPP - linear regression.
+/* PSPP - a program for statistical analysis.
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 the Free Software Foundation; either version 2 of the
- License, or (at your option) any later version.
+ 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.
+ 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
- 02110-1301, USA. */
+ along with this program. If not, see . */
#include
@@ -119,14 +117,14 @@ static size_t n_variables;
/*
File where the model will be saved if the EXPORT subcommand
- is given.
+ is given.
*/
static struct file_handle *model_file;
static bool run_regression (struct casereader *, struct cmd_regression *,
- struct dataset *);
+ struct dataset *);
-/*
+/*
STATISTICS subcommand output functions.
*/
static void reg_stats_r (pspp_linreg_cache *);
@@ -454,8 +452,8 @@ statistics_keyword_output (void (*function) (pspp_linreg_cache *),
static void
subcommand_statistics (int *keywords, pspp_linreg_cache * c)
{
- /*
- The order here must match the order in which the STATISTICS
+ /*
+ The order here must match the order in which the STATISTICS
keywords appear in the specification section above.
*/
enum
@@ -628,7 +626,7 @@ regression_trns_resid_proc (void *t_, struct ccase *c,
return TRNS_CONTINUE;
}
-/*
+/*
Returns false if NAME is a duplicate of any existing variable name.
*/
static bool
@@ -1014,7 +1012,8 @@ regression_custom_variables (struct lexer *lexer, struct dataset *ds,
/* Identify the explanatory variables in v_variables. Returns
the number of independent variables. */
static int
-identify_indep_vars (const struct variable **indep_vars, const struct variable *depvar)
+identify_indep_vars (const struct variable **indep_vars,
+ const struct variable *depvar)
{
int n_indep_vars = 0;
int i;
@@ -1030,8 +1029,8 @@ identify_indep_vars (const struct variable **indep_vars, const struct variable *
Returns number of valid cases. */
static int
prepare_categories (struct casereader *input,
- const struct variable **vars, size_t n_vars,
- struct moments_var *mom)
+ const struct variable **vars, size_t n_vars,
+ struct moments_var *mom)
{
int n_data;
struct ccase c;
@@ -1042,23 +1041,23 @@ prepare_categories (struct casereader *input,
cat_stored_values_create (vars[i]);
n_data = 0;
- for (; casereader_read (input, &c); case_destroy (&c))
+ for (; casereader_read (input, &c); case_destroy (&c))
{
/*
- The second condition ensures the program will run even if
- there is only one variable to act as both explanatory and
- response.
+ The second condition ensures the program will run even if
+ there is only one variable to act as both explanatory and
+ response.
*/
for (i = 0; i < n_vars; i++)
- {
- const union value *val = case_data (&c, vars[i]);
- if (var_is_alpha (vars[i]))
- cat_value_update (vars[i], val);
- else
- moments1_add (mom[i].m, val->f, 1.0);
- }
- n_data++;
- }
+ {
+ const union value *val = case_data (&c, vars[i]);
+ if (var_is_alpha (vars[i]))
+ cat_value_update (vars[i], val);
+ else
+ moments1_add (mom[i].m, val->f, 1.0);
+ }
+ n_data++;
+ }
casereader_destroy (input);
return n_data;
@@ -1108,7 +1107,7 @@ compute_moments (pspp_linreg_cache * c, struct moments_var *mom,
static bool
run_regression (struct casereader *input, struct cmd_regression *cmd,
- struct dataset *ds)
+ struct dataset *ds)
{
size_t i;
int n_indep = 0;
@@ -1161,17 +1160,17 @@ run_regression (struct casereader *input, struct cmd_regression *cmd,
casenumber row;
struct ccase c;
size_t n_data; /* Number of valid cases. */
-
+
dep_var = cmd->v_dependent[k];
n_indep = identify_indep_vars (indep_vars, dep_var);
reader = casereader_clone (input);
reader = casereader_create_filter_missing (reader, indep_vars, n_indep,
- MV_ANY, NULL);
+ MV_ANY, NULL);
reader = casereader_create_filter_missing (reader, &dep_var, 1,
- MV_ANY, NULL);
- n_data = prepare_categories (casereader_clone (reader),
- indep_vars, n_indep, mom);
+ MV_ANY, NULL);
+ n_data = prepare_categories (casereader_clone (reader),
+ indep_vars, n_indep, mom);
if ((n_data > 0) && (n_indep > 0))
{
@@ -1187,33 +1186,32 @@ run_regression (struct casereader *input, struct cmd_regression *cmd,
models[k] = pspp_linreg_cache_alloc (X->m->size1, X->m->size2);
models[k]->indep_means = gsl_vector_alloc (X->m->size2);
models[k]->indep_std = gsl_vector_alloc (X->m->size2);
- models[k]->depvar = dep_var;
- /*
+ models[k]->depvar = dep_var;
+ /*
For large data sets, use QR decomposition.
*/
if (n_data > sqrt (n_indep) && n_data > REG_LARGE_DATA)
{
- models[k]->method = PSPP_LINREG_SVD;
+ models[k]->method = PSPP_LINREG_QR;
}
/*
- The second pass fills the design matrix.
- */
- reader = casereader_create_counter (reader, &row, -1);
- for (; casereader_read (reader, &c); case_destroy (&c))
- {
- for (i = 0; i < n_indep; ++i)
- {
- const struct variable *v = indep_vars[i];
- const union value *val = case_data (&c, v);
- if (var_is_alpha (v))
- design_matrix_set_categorical (X, row, v, val);
- else
- design_matrix_set_numeric (X, row, v, val);
- }
- gsl_vector_set (Y, row, case_num (&c, dep_var));
- }
- casereader_destroy (reader);
+ The second pass fills the design matrix.
+ */
+ reader = casereader_create_counter (reader, &row, -1);
+ for (; casereader_read (reader, &c); case_destroy (&c))
+ {
+ for (i = 0; i < n_indep; ++i)
+ {
+ const struct variable *v = indep_vars[i];
+ const union value *val = case_data (&c, v);
+ if (var_is_alpha (v))
+ design_matrix_set_categorical (X, row, v, val);
+ else
+ design_matrix_set_numeric (X, row, v, val);
+ }
+ gsl_vector_set (Y, row, case_num (&c, dep_var));
+ }
/*
Now that we know the number of coefficients, allocate space
and store pointers to the variables that correspond to the
@@ -1221,25 +1219,27 @@ run_regression (struct casereader *input, struct cmd_regression *cmd,
*/
coeff_init (models[k], X);
- /*
+ /*
Find the least-squares estimates and other statistics.
*/
pspp_linreg ((const gsl_vector *) Y, X->m, &lopts, models[k]);
compute_moments (models[k], mom, X, n_variables);
- if (!taint_has_tainted_successor (casereader_get_taint (input)))
- {
- subcommand_statistics (cmd->a_statistics, models[k]);
- subcommand_export (cmd->sbc_export, models[k]);
- }
+ if (!taint_has_tainted_successor (casereader_get_taint (input)))
+ {
+ subcommand_statistics (cmd->a_statistics, models[k]);
+ subcommand_export (cmd->sbc_export, models[k]);
+ }
gsl_vector_free (Y);
design_matrix_destroy (X);
}
else
{
- msg (SE, gettext ("No valid data found. This command was skipped."));
+ msg (SE,
+ gettext ("No valid data found. This command was skipped."));
}
+ casereader_destroy (reader);
}
free (indep_vars);
free (lopts.get_indep_mean_std);
@@ -1249,7 +1249,7 @@ run_regression (struct casereader *input, struct cmd_regression *cmd,
}
/*
- Local Variables:
+ Local Variables:
mode: c
End:
*/