X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;ds=sidebyside;f=src%2Fregression.q;h=ee7c0075442288cc32afb9e2aa9f8ff48982cd64;hb=5ff91bd55867848d448c2f09bc7057cc1fb77b18;hp=56420c5335e964dd20ee7a3de9a21aa484fd6aa3;hpb=7b80235141f331530de337cceeab87de873c5cc2;p=pspp diff --git a/src/regression.q b/src/regression.q index 56420c5335..ee7c007544 100644 --- a/src/regression.q +++ b/src/regression.q @@ -33,6 +33,7 @@ #include "gettext.h" #include "lexer.h" #include +#include "missing-values.h" #include "tab.h" #include "var.h" #include "vfm.h" @@ -151,7 +152,7 @@ reg_stats_coeff (pspp_linreg_cache * c) 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); @@ -167,7 +168,7 @@ reg_stats_coeff (pspp_linreg_cache * c) 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); @@ -177,40 +178,39 @@ reg_stats_coeff (pspp_linreg_cache * c) 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); @@ -500,101 +500,130 @@ run_regression (const struct casefile *cf, void *cmd_ UNUSED) 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++; } } /* @@ -608,6 +637,7 @@ run_regression (const struct casefile *cf, void *cmd_ UNUSED) 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. @@ -619,6 +649,7 @@ run_regression (const struct casefile *cf, void *cmd_ UNUSED) pspp_linreg_cache_free (lcache); free (lopts.get_indep_mean_std); free (indep_vars); + free (is_missing_case); casereader_destroy (r); return; }