#include "gettext.h"
#include "lexer.h"
#include <linreg/pspp_linreg.h>
+#include "missing-values.h"
#include "tab.h"
#include "var.h"
#include "vfm.h"
struct tab_table *t;
assert (c != NULL);
- n_rows = 2;
+ n_rows = c->n_coeffs + 2;
t = tab_create (n_cols, n_rows, 0);
tab_headers (t, 2, 0, 1, 0);
tab_text (t, 5, 0, TAB_CENTER | TAT_TITLE, _("t"));
tab_text (t, 6, 0, TAB_CENTER | TAT_TITLE, _("Significance"));
tab_text (t, 1, 1, TAB_LEFT | TAT_TITLE, _("(Constant)"));
- coeff = gsl_vector_get (c->param_estimates, 0);
+ coeff = c->coeff[0].estimate;
tab_float (t, 2, 1, 0, coeff, 10, 2);
std_err = sqrt (gsl_matrix_get (c->cov, 0, 0));
tab_float (t, 3, 1, 0, std_err, 10, 2);
tab_float (t, 5, 1, 0, t_stat, 10, 2);
pval = 2 * gsl_cdf_tdist_Q (fabs (t_stat), 1.0);
tab_float (t, 6, 1, 0, pval, 10, 2);
- for (j = 0; j < c->n_indeps; j++)
+ for (j = 1; j <= c->n_indeps; j++)
{
i = indep_vars[j];
- struct variable *v = cmd.v_variables[i];
- label = var_to_string (v);
- tab_text (t, 1, j + 2, TAB_CENTER, label);
+ label = var_to_string (c->coeff[j].v);
+ tab_text (t, 1, j + 1, TAB_CENTER, label);
/*
Regression coefficients.
*/
- coeff = gsl_vector_get (c->param_estimates, j + 1);
- tab_float (t, 2, j + 2, 0, coeff, 10, 2);
+ coeff = c->coeff[j].estimate;
+ tab_float (t, 2, j + 1, 0, coeff, 10, 2);
/*
Standard error of the coefficients.
*/
- std_err = sqrt (gsl_matrix_get (c->cov, j + 1, j + 1));
- tab_float (t, 3, j + 2, 0, std_err, 10, 2);
+ std_err = sqrt (gsl_matrix_get (c->cov, j, j));
+ tab_float (t, 3, j + 1, 0, std_err, 10, 2);
/*
'Standardized' coefficient, i.e., regression coefficient
if all variables had unit variance.
*/
- beta = gsl_vector_get (c->indep_std, j + 1);
+ beta = gsl_vector_get (c->indep_std, j);
beta *= coeff / c->depvar_std;
- tab_float (t, 4, j + 2, 0, beta, 10, 2);
+ tab_float (t, 4, j + 1, 0, beta, 10, 2);
/*
Test statistic for H0: coefficient is 0.
*/
t_stat = coeff / std_err;
- tab_float (t, 5, j + 2, 0, t_stat, 10, 2);
+ tab_float (t, 5, j + 1, 0, t_stat, 10, 2);
/*
P values for the test statistic above.
*/
pval = 2 * gsl_cdf_tdist_Q (fabs (t_stat), 1.0);
- tab_float (t, 6, j + 2, 0, pval, 10, 2);
+ tab_float (t, 6, j + 1, 0, pval, 10, 2);
}
tab_title (t, 0, _("Coefficients"));
tab_submit (t);
size_t k;
size_t n_data = 0;
size_t row;
+ size_t case_num;
int n_indep;
int j = 0;
+ /*
+ Keep track of the missing cases.
+ */
+ int *is_missing_case;
const union value *val;
struct casereader *r;
struct casereader *r2;
struct ccase c;
- const struct variable *v;
- struct recoded_categorical_array *ca;
- struct recoded_categorical *rc;
+ struct variable *v;
struct design_matrix *X;
gsl_vector *Y;
pspp_linreg_cache *lcache;
pspp_linreg_opts lopts;
n_data = casefile_get_case_cnt (cf);
+
+ is_missing_case = xnmalloc (n_data, sizeof (*is_missing_case));
+ for (i = 0; i < n_data; i++)
+ is_missing_case[i] = 0;
+
n_indep = cmd.n_variables - cmd.n_dependent;
indep_vars = xnmalloc (n_indep, sizeof *indep_vars);
- Y = gsl_vector_alloc (n_data);
lopts.get_depvar_mean_std = 1;
lopts.get_indep_mean_std = xnmalloc (n_indep, sizeof (int));
- lcache = pspp_linreg_cache_alloc (n_data, n_indep);
- lcache->indep_means = gsl_vector_alloc (n_indep);
- lcache->indep_std = gsl_vector_alloc (n_indep);
/*
Read from the active file. The first pass encodes categorical
- variables.
+ variables and drops cases with missing values.
*/
- ca = cr_recoded_cat_ar_create (cmd.n_variables, cmd.v_variables);
- for (r = casefile_get_reader (cf);
- casereader_read (r, &c); case_destroy (&c))
+ for (i = 0; i < cmd.n_variables; i++)
{
- for (i = 0; i < ca->n_vars; i++)
+ v = cmd.v_variables[i];
+ if (v->type == ALPHA)
{
- v = (*(ca->a + i))->v;
+ /* Make a place to hold the binary vectors
+ corresponding to this variable's values. */
+ cat_stored_values_create (v);
+ }
+ for (r = casefile_get_reader (cf);
+ casereader_read (r, &c); case_destroy (&c))
+ {
+ row = casereader_cnum (r) - 1;
+
val = case_data (&c, v->fv);
- cr_value_update (*(ca->a + i), val);
+ cat_value_update (v, val);
+ if (mv_is_value_missing (&v->miss, val))
+ {
+ if (!is_missing_case[row])
+ {
+ /* Now it is missing. */
+ n_data--;
+ is_missing_case[row] = 1;
+ }
+ }
}
}
- cr_create_value_matrices (ca);
+
+ Y = gsl_vector_alloc (n_data);
X =
design_matrix_create (n_indep, (const struct variable **) cmd.v_variables,
- ca, n_data);
+ n_data);
+ lcache = pspp_linreg_cache_alloc (X->m->size1, X->m->size2);
+ lcache->indep_means = gsl_vector_alloc (X->m->size2);
+ lcache->indep_std = gsl_vector_alloc (X->m->size2);
/*
The second pass creates the design matrix.
*/
+ row = 0;
for (r2 = casefile_get_reader (cf); casereader_read (r2, &c);
case_destroy (&c))
/* Iterate over the cases. */
{
k = 0;
- row = casereader_cnum (r2) - 1;
- for (i = 0; i < cmd.n_variables; ++i) /* Iterate over the variables
+ case_num = casereader_cnum (r2) - 1;
+ if (!is_missing_case[case_num])
+ {
+ for (i = 0; i < cmd.n_variables; ++i) /* Iterate over the variables
for the current case.
*/
- {
- v = cmd.v_variables[i];
- val = case_data (&c, v->fv);
- /*
- Independent/dependent variable separation. The
- 'variables' subcommand specifies a varlist which contains
- both dependent and independent variables. The dependent
- variables are specified with the 'dependent'
- subcommand. We need to separate the two.
- */
- if (is_depvar (i))
{
- if (v->type != NUMERIC)
+ v = cmd.v_variables[i];
+ val = case_data (&c, v->fv);
+ /*
+ Independent/dependent variable separation. The
+ 'variables' subcommand specifies a varlist which contains
+ both dependent and independent variables. The dependent
+ variables are specified with the 'dependent'
+ subcommand. We need to separate the two.
+ */
+ if (is_depvar (i))
{
- msg (SE, gettext ("Dependent variable must be numeric."));
- pspp_reg_rc = CMD_FAILURE;
- return;
+ if (v->type != NUMERIC)
+ {
+ msg (SE,
+ gettext ("Dependent variable must be numeric."));
+ pspp_reg_rc = CMD_FAILURE;
+ return;
+ }
+ lcache->depvar = (const struct var *) v;
+ gsl_vector_set (Y, row, val->f);
}
- lcache->depvar = (const struct var *) v;
- gsl_vector_set (Y, row, val->f);
- }
- else
- {
- if (v->type == ALPHA)
+ else
{
- rc = cr_var_to_recoded_categorical (v, ca);
- design_matrix_set_categorical (X, row, v, val, rc);
+ if (v->type == ALPHA)
+ {
+ design_matrix_set_categorical (X, row, v, val);
+ }
+ else if (v->type == NUMERIC)
+ {
+ design_matrix_set_numeric (X, row, v, val);
+ }
+
+ indep_vars[k] = i;
+ k++;
+ lopts.get_indep_mean_std[i] = 1;
}
- else if (v->type == NUMERIC)
- {
- design_matrix_set_numeric (X, row, v, val);
- }
-
- indep_vars[k] = i;
- k++;
- lopts.get_indep_mean_std[i] = 1;
}
+ row++;
}
}
/*
j = i + 1; /* The first coeff is the intercept. */
lcache->coeff[j].v =
(const struct variable *) design_matrix_col_to_var (X, i);
+ assert (lcache->coeff[j].v != NULL);
}
/*
Find the least-squares estimates and other statistics.
pspp_linreg_cache_free (lcache);
free (lopts.get_indep_mean_std);
free (indep_vars);
+ free (is_missing_case);
casereader_destroy (r);
return;
}
projects / pspp-builds.git / blobdiff