all;
export=custom;
^dependent=varlist;
- save=residuals;
+ save[sv_]=resid,pred;
method=enter.
*/
/* (declarations) */
/* Linear regression models. */
pspp_linreg_cache **models = NULL;
+/*
+ Transformations for saving predicted values
+ and residuals, etc.
+ */
+struct reg_trns
+{
+ int n_trns; /* Number of transformations. */
+ int trns_id; /* Which trns is this one? */
+ pspp_linreg_cache *c; /* Linear model for this trns. */
+};
/*
Variables used (both explanatory and response).
*/
statistics_keyword_output (reg_stats_tol, keywords[tol], c);
statistics_keyword_output (reg_stats_selection, keywords[selection], c);
}
+/*
+ Free the transformation. Free its linear model if this
+ transformation is the last one.
+ */
+static
+bool regression_trns_free (void *t_)
+{
+ bool result = true;
+ struct reg_trns *t = t_;
+
+ if (t->trns_id == t->n_trns)
+ {
+ result = pspp_linreg_cache_free (t->c);
+ }
+ free (t);
+
+ return result;
+}
+/*
+ Gets the predicted values.
+ */
static int
-regression_trns_proc (void *m, struct ccase *c, int case_idx UNUSED)
+regression_trns_pred_proc (void *t_, struct ccase *c, int case_idx UNUSED)
{
size_t i;
size_t n_vars;
size_t n_vals = 0;
- pspp_linreg_cache *model = m;
+ union value *tmp = NULL;
+ struct reg_trns *t = t_;
+ pspp_linreg_cache *model;
union value *output;
const union value **vals = NULL;
- const union value *obs = NULL;
struct variable **vars = NULL;
+ struct variable **model_vars = NULL;
+ assert (t != NULL);
+ model = t->c;
assert (model != NULL);
assert (model->depvar != NULL);
- assert (model->resid != NULL);
+ assert (model->pred != NULL);
dict_get_vars (default_dict, &vars, &n_vars, 1u << DC_SYSTEM);
vals = xnmalloc (n_vars, sizeof (*vals));
+ model_vars = xnmalloc (n_vars, sizeof (*model_vars));
assert (vals != NULL);
- output = case_data_rw (c, model->resid->fv);
+ output = case_data_rw (c, model->pred->fv);
assert (output != NULL);
for (i = 0; i < n_vars; i++)
{
- /* Do not use the residual variable. */
- if (vars[i]->index != model->resid->index)
+ /* Use neither the predicted values nor the dependent variable. */
+ if (vars[i]->index != model->pred->index &&
+ vars[i]->index != model->depvar->index)
{
- /* Do not use the dependent variable as a predictor. */
- if (vars[i]->index == model->depvar->index)
+ if (vars[i]->type == ALPHA && vars[i]->obs_vals != NULL)
+ {
+ tmp = vars[i]->obs_vals->vals;
+ }
+ else
{
- obs = case_data (c, i);
- assert (obs != NULL);
+ tmp = NULL;
}
- else
+ /*
+ Make sure the variable we use is in the linear model.
+ */
+ if (pspp_linreg_get_coeff (model, vars[i], tmp) != NULL)
{
- vals[i] = case_data (c, i);
+ vals[n_vals] = case_data (c, i);
+ model_vars[n_vals] = vars[i];
n_vals++;
}
}
}
+ output->f = (*model->predict) ((const struct variable **) vars,
+ vals, model, n_vals);
+ free (vals);
+ free (model_vars);
+ return TRNS_CONTINUE;
+}
+/*
+ Gets the residuals.
+ */
+static int
+regression_trns_resid_proc (void *t_, struct ccase *c, int case_idx UNUSED)
+{
+ size_t i;
+ size_t n_vars;
+ size_t n_vals = 0;
+ struct reg_trns *t = t_;
+ pspp_linreg_cache *model;
+ union value *output;
+ union value *tmp;
+ const union value **vals = NULL;
+ const union value *obs = NULL;
+ struct variable **vars = NULL;
+ struct variable **model_vars = NULL;
+
+ assert (t!= NULL);
+ model = t->c;
+ assert (model != NULL);
+ assert (model->depvar != NULL);
+ assert (model->resid != NULL);
+
+ dict_get_vars (default_dict, &vars, &n_vars, 1u << DC_SYSTEM);
+ vals = xnmalloc (n_vars, sizeof (*vals));
+ model_vars = xnmalloc (n_vars, sizeof (*model_vars));
+ assert (vals != NULL);
+ output = case_data_rw (c, model->resid->fv);
+ assert (output != NULL);
+
+ for (i = 0; i < n_vars; i++)
+ {
+ /* Use neither the predicted values nor the dependent variable. */
+ if (vars[i]->index != model->resid->index &&
+ vars[i]->index != model->depvar->index)
+ {
+ if (vars[i]->type == ALPHA && vars[i]->obs_vals != NULL)
+ {
+ tmp = vars[i]->obs_vals->vals;
+ }
+ else
+ {
+ tmp = NULL;
+ }
+ /*
+ Make sure the variable we use is in the linear model.
+ */
+ if (pspp_linreg_get_coeff (model, vars[i], tmp) != NULL)
+ {
+ vals[n_vals] = case_data (c, i);
+ model_vars[n_vals] = vars[i];
+ n_vals++;
+ }
+ }
+ if (vars[i]->index == model->depvar->index)
+ {
+ obs = case_data (c, i);
+ assert (obs != NULL);
+ }
+ }
output->f = (*model->residual) ((const struct variable **) vars,
vals, obs, model, n_vals);
free (vals);
+ free (model_vars);
return TRNS_CONTINUE;
}
+/*
+ Returns 0 if NAME is a duplicate of any existing variable name.
+*/
+static int
+try_name (char *name)
+{
+ if (dict_lookup_var (default_dict, name) != NULL)
+ return 0;
+
+ return 1;
+}
+static
+void reg_get_name (char name[LONG_NAME_LEN], const char prefix[LONG_NAME_LEN])
+{
+ int i = 1;
+
+ snprintf (name, LONG_NAME_LEN, "%s%d", prefix, i);
+ while (!try_name(name))
+ {
+ i++;
+ snprintf (name, LONG_NAME_LEN, "%s%d", prefix, i);
+ }
+}
+static void
+reg_save_var (const char *prefix, trns_proc_func *f,
+ pspp_linreg_cache *c, struct variable **v,
+ int n_trns)
+{
+ static int trns_index = 1;
+ char name[LONG_NAME_LEN + 1];
+ struct variable *new_var;
+ struct reg_trns *t = NULL;
+
+ t = xmalloc (sizeof (*t));
+ assert (t != NULL);
+ t->trns_id = trns_index;
+ t->n_trns = n_trns;
+ t->c = c;
+ reg_get_name (name, prefix);
+ new_var = dict_create_var (default_dict, name, 0);
+ assert (new_var != NULL);
+ *v = new_var;
+ add_transformation (f, regression_trns_free, t);
+ trns_index++;
+}
static void
subcommand_save (int save, pspp_linreg_cache **models)
{
- struct variable *residuals = NULL;
pspp_linreg_cache **lc;
+ int n_trns = 0;
+ int i;
assert (models != NULL);
if (save)
{
+ /* Count the number of transformations we will need. */
+ for (i = 0; i < REGRESSION_SV_count; i++)
+ {
+ if (cmd.a_save[i])
+ {
+ n_trns++;
+ }
+ }
+ n_trns *= cmd.n_dependent;
+
for (lc = models; lc < models + cmd.n_dependent; lc++)
{
assert (*lc != NULL);
assert ((*lc)->depvar != NULL);
- residuals = dict_create_var (default_dict, "residuals", 0);
- assert (residuals != NULL);
- (*lc)->resid = residuals;
- add_transformation (regression_trns_proc, pspp_linreg_cache_free, *lc);
+ if (cmd.a_save[REGRESSION_SV_RESID])
+ {
+ reg_save_var ("RES", regression_trns_resid_proc, *lc, &(*lc)->resid, n_trns);
+ }
+ if (cmd.a_save[REGRESSION_SV_PRED])
+ {
+ reg_save_var ("PRED", regression_trns_pred_proc, *lc, &(*lc)->pred, n_trns);
+ }
}
}
else