/* (specification)
"REGRESSION" (regression_):
*variables=custom;
- statistics[st_]=r,
- coeff,
- anova,
- outs,
- zpp,
- label,
- sha,
- ci,
- bcov,
- ses,
- xtx,
- collin,
- tol,
- selection,
- f,
- defaults,
- all;
+ +statistics[st_]=r,
+ coeff,
+ anova,
+ outs,
+ zpp,
+ label,
+ sha,
+ ci,
+ bcov,
+ ses,
+ xtx,
+ collin,
+ tol,
+ selection,
+ f,
+ defaults,
+ all;
export=custom;
^dependent=varlist;
- save[sv_]=resid,pred;
- method=enter.
+ +save[sv_]=resid,pred;
+ +method=enter.
*/
/* (declarations) */
/* (functions) */
static struct cmd_regression cmd;
/* Linear regression models. */
-pspp_linreg_cache **models = NULL;
+static pspp_linreg_cache **models = NULL;
/*
Transformations for saving predicted values
File where the model will be saved if the EXPORT subcommand
is given.
*/
-struct file_handle *model_file;
+static struct file_handle *model_file;
/*
Return value for the procedure.
*/
-int pspp_reg_rc = CMD_SUCCESS;
+static int pspp_reg_rc = CMD_SUCCESS;
static bool run_regression (const struct ccase *,
- const struct casefile *, void *);
+ const struct casefile *, void *);
/*
STATISTICS subcommand output functions.
tab_float (t, 6, 1, 0, pval, 10, 2);
for (j = 1; j <= c->n_indeps; j++)
{
- v = pspp_linreg_coeff_get_var (c->coeff[j], 0);
+ v = pspp_coeff_get_var (c->coeff[j], 0);
label = var_to_string (v);
/* Do not overwrite the variable's name. */
strncpy (tmp, label, MAX_STRING);
for that value.
*/
- val = pspp_linreg_coeff_get_value (c->coeff[j], v);
+ val = pspp_coeff_get_value (c->coeff[j], v);
val_s = value_to_string (val, v);
strncat (tmp, val_s, MAX_STRING);
}
tab_text (t, 1, 1, TAB_CENTER | TAT_TITLE, _("Covariances"));
for (i = 1; i < c->n_coeffs; i++)
{
- const struct variable *v = pspp_linreg_coeff_get_var (c->coeff[i], 0);
+ const struct variable *v = pspp_coeff_get_var (c->coeff[i], 0);
label = var_to_string (v);
tab_text (t, 2, i, TAB_CENTER, label);
tab_text (t, i + 2, 0, TAB_CENTER, label);
Gets the predicted values.
*/
static int
-regression_trns_pred_proc (void *t_, struct ccase *c, int case_idx UNUSED)
+regression_trns_pred_proc (void *t_, struct ccase *c,
+ casenum_t case_idx UNUSED)
{
size_t i;
size_t n_vals;
Gets the residuals.
*/
static int
-regression_trns_resid_proc (void *t_, struct ccase *c, int case_idx UNUSED)
+regression_trns_resid_proc (void *t_, struct ccase *c,
+ casenum_t case_idx UNUSED)
{
size_t i;
size_t n_vals;
static int
try_name (char *name)
{
- if (dict_lookup_var (default_dict, name) != NULL)
+ if (dict_lookup_var (dataset_dict (current_dataset), name) != NULL)
return 0;
return 1;
t->n_trns = n_trns;
t->c = c;
reg_get_name (name, prefix);
- new_var = dict_create_var (default_dict, name, 0);
+ new_var = dict_create_var (dataset_dict (current_dataset), name, 0);
assert (new_var != NULL);
*v = new_var;
- add_transformation (f, regression_trns_free, t);
+ add_transformation (current_dataset, f, regression_trns_free, t);
trns_index++;
}
static void
size_t j;
int n_vars = 0;
struct variable **varlist;
- struct pspp_linreg_coeff *coeff;
+ struct pspp_coeff *coeff;
const struct variable *v;
union value *val;
for (i = 1; i < c->n_indeps; i++) /* c->coeff[0] is the intercept. */
{
coeff = c->coeff[i];
- v = pspp_linreg_coeff_get_var (coeff, 0);
+ v = pspp_coeff_get_var (coeff, 0);
if (v->type == ALPHA)
{
if (!reg_inserted (v, varlist, n_vars))
reg_print_depvars (FILE * fp, pspp_linreg_cache * c)
{
int i;
- struct pspp_linreg_coeff *coeff;
+ struct pspp_coeff *coeff;
const struct variable *v;
fprintf (fp, "char *model_depvars[%d] = {", c->n_indeps);
for (i = 1; i < c->n_indeps; i++)
{
coeff = c->coeff[i];
- v = pspp_linreg_coeff_get_var (coeff, 0);
+ v = pspp_coeff_get_var (coeff, 0);
fprintf (fp, "\"%s\",\n\t\t", v->name);
}
coeff = c->coeff[i];
- v = pspp_linreg_coeff_get_var (coeff, 0);
+ v = pspp_coeff_get_var (coeff, 0);
fprintf (fp, "\"%s\"};\n\t", v->name);
}
static void
for (i = 1; i < c->n_coeffs; i++)
{
- v = pspp_linreg_coeff_get_var (c->coeff[i], 0);
+ v = pspp_coeff_get_var (c->coeff[i], 0);
if (v->type == ALPHA)
{
return 1;
size_t i;
size_t j;
int n_quantiles = 100;
- double increment;
double tmp;
- struct pspp_linreg_coeff *coeff;
+ struct pspp_coeff *coeff;
if (export)
{
reg_print_categorical_encoding (fp, c);
}
fprintf (fp, "%s", reg_export_t_quantiles_1);
- increment = 0.5 / (double) increment;
for (i = 0; i < n_quantiles - 1; i++)
{
tmp = 0.5 + 0.005 * (double) i;
}
}
static int
-regression_custom_export (struct cmd_regression *cmd UNUSED)
+regression_custom_export (struct cmd_regression *cmd UNUSED, void *aux UNUSED)
{
/* 0 on failure, 1 on success, 2 on failure that should result in syntax error */
if (!lex_force_match ('('))
int
cmd_regression (void)
{
- if (!parse_regression (&cmd))
+ if (!parse_regression (&cmd, NULL))
return CMD_FAILURE;
models = xnmalloc (cmd.n_dependent, sizeof *models);
- if (!multipass_procedure_with_splits (run_regression, &cmd))
+ if (!multipass_procedure_with_splits (current_dataset, run_regression, &cmd))
return CMD_CASCADING_FAILURE;
subcommand_save (cmd.sbc_save, models);
free (v_variables);
/*
Is variable k the dependent variable?
*/
-static int
+static bool
is_depvar (size_t k, const struct variable *v)
{
/*
names match.
*/
if (!compare_var_names (v, v_variables[k], NULL))
- return 1;
+ return true;
- return 0;
+ return false;
}
/*
/* Parser for the variables sub command */
static int
-regression_custom_variables (struct cmd_regression *cmd UNUSED)
+regression_custom_variables (struct cmd_regression *cmd UNUSED,
+ void *aux UNUSED)
{
lex_match ('=');
- if ((token != T_ID || dict_lookup_var (default_dict, tokid) == NULL)
+ if ((token != T_ID || dict_lookup_var (dataset_dict (current_dataset), tokid) == NULL)
&& token != T_ALL)
return 2;
- if (!parse_variables (default_dict, &v_variables, &n_variables, PV_NONE))
+ if (!parse_variables (dataset_dict (current_dataset), &v_variables, &n_variables, PV_NONE))
{
free (v_variables);
return 0;
return n_data;
}
+static void
+coeff_init (pspp_linreg_cache * c, struct design_matrix *dm)
+{
+ c->coeff = xnmalloc (dm->m->size2 + 1, sizeof (*c->coeff));
+ c->coeff[0] = xmalloc (sizeof (*(c->coeff[0]))); /* The first coefficient is the intercept. */
+ c->coeff[0]->v_info = NULL; /* Intercept has no associated variable. */
+ pspp_coeff_init (c->coeff + 1, dm);
+}
static bool
run_regression (const struct ccase *first,
- const struct casefile *cf, void *cmd_ UNUSED)
+ const struct casefile *cf, void *cmd_ UNUSED)
{
size_t i;
size_t n_data = 0; /* Number of valide cases. */
if (!v_variables)
{
- dict_get_vars (default_dict, &v_variables, &n_variables,
+ dict_get_vars (dataset_dict (current_dataset), &v_variables, &n_variables,
1u << DC_SYSTEM);
}
and store pointers to the variables that correspond to the
coefficients.
*/
- pspp_linreg_coeff_init (models[k], X);
+ coeff_init (models[k], X);
/*
Find the least-squares estimates and other statistics.
projects / pspp-builds.git / blobdiff