From: Jason Stover Date: Wed, 26 Apr 2006 19:16:07 +0000 (+0000) Subject: added support for saving residuals and predicted values X-Git-Tag: v0.6.0~944 X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=commitdiff_plain;h=08703a888d1cc31459e6028a61e3940f6d4b2c5f;p=pspp-builds.git added support for saving residuals and predicted values --- diff --git a/src/language/stats/ChangeLog b/src/language/stats/ChangeLog index 7387333b..497e5de9 100644 --- a/src/language/stats/ChangeLog +++ b/src/language/stats/ChangeLog @@ -1,3 +1,20 @@ +2006-04-26 Jason Stover + + * regression.q: Added support for multiple transformations. + + * regression.q (regression_trns_resid_proc): New function. + + * regression.q (regression_trns_pred_proc): New function. + + * regression.q (subcommand_save): Added support for saving + predicted values. + + * regression.q (regression_trns_free): New function. + + * regression.q (reg_get_name): New function. + + * regression.q (reg_save_var): New function. + Tue Apr 25 13:18:56 2006 Ben Pfaff * rank.q (parse_rank_function): Use SE instead of ME for parse diff --git a/src/language/stats/regression.q b/src/language/stats/regression.q index 34aef922..c7dc7d50 100644 --- a/src/language/stats/regression.q +++ b/src/language/stats/regression.q @@ -71,7 +71,7 @@ all; export=custom; ^dependent=varlist; - save=residuals; + save[sv_]=resid,pred; method=enter. */ /* (declarations) */ @@ -81,6 +81,16 @@ static struct cmd_regression cmd; /* 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). */ @@ -504,49 +514,150 @@ subcommand_statistics (int *keywords, pspp_linreg_cache * c) 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; } /* @@ -560,34 +671,73 @@ try_name (char *name) 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) { - int i; - char name[LONG_NAME_LEN + 1]; - struct variable *residuals = NULL; pspp_linreg_cache **lc; + int n_trns = 0; + int i; assert (models != NULL); if (save) { - i = 1; - snprintf (name, LONG_NAME_LEN, "RES%d", i); + /* 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); - while (!try_name (name)) + 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]) { - i++; - snprintf (name, LONG_NAME_LEN, "RES%d", i); + reg_save_var ("PRED", regression_trns_pred_proc, *lc, &(*lc)->pred, n_trns); } - residuals = dict_create_var (default_dict, name, 0); - assert (residuals != NULL); - (*lc)->resid = residuals; - add_transformation (regression_trns_proc, pspp_linreg_cache_free, *lc); } } else