X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Flanguage%2Fstats%2Fregression.q;h=2c259d0f904c1834c7d7e1614fe4f47084bab5ee;hb=2cf38ce51a9f34961d68a75e0b312a591b5c9abf;hp=68db454d40edfbc38316884903f893227fd9bc0b;hpb=9a331fe64eb814ae5c1322e21717a04fb254bf65;p=pspp-builds.git diff --git a/src/language/stats/regression.q b/src/language/stats/regression.q index 68db454d..2c259d0f 100644 --- a/src/language/stats/regression.q +++ b/src/language/stats/regression.q @@ -150,7 +150,7 @@ reg_stats_r (pspp_linreg_cache * c) adjrsq = 1.0 - (1.0 - rsq) * (c->n_obs - 1.0) / (c->n_obs - c->n_indeps); std_error = sqrt (pspp_linreg_mse (c)); t = tab_create (n_cols, n_rows, 0); - tab_dim (t, tab_natural_dimensions); + tab_dim (t, tab_natural_dimensions, NULL); tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, n_cols - 1, n_rows - 1); tab_hline (t, TAL_2, 0, n_cols - 1, 1); tab_vline (t, TAL_2, 2, 0, n_rows - 1); @@ -160,10 +160,10 @@ reg_stats_r (pspp_linreg_cache * c) tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("R Square")); tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Adjusted R Square")); tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("Std. Error of the Estimate")); - tab_float (t, 1, 1, TAB_RIGHT, sqrt (rsq), 10, 2); - tab_float (t, 2, 1, TAB_RIGHT, rsq, 10, 2); - tab_float (t, 3, 1, TAB_RIGHT, adjrsq, 10, 2); - tab_float (t, 4, 1, TAB_RIGHT, std_error, 10, 2); + tab_double (t, 1, 1, TAB_RIGHT, sqrt (rsq), NULL); + tab_double (t, 2, 1, TAB_RIGHT, rsq, NULL); + tab_double (t, 3, 1, TAB_RIGHT, adjrsq, NULL); + tab_double (t, 4, 1, TAB_RIGHT, std_error, NULL); tab_title (t, _("Model Summary")); tab_submit (t); } @@ -193,7 +193,7 @@ reg_stats_coeff (pspp_linreg_cache * c) t = tab_create (n_cols, n_rows, 0); tab_headers (t, 2, 0, 1, 0); - tab_dim (t, tab_natural_dimensions); + tab_dim (t, tab_natural_dimensions, NULL); tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, n_cols - 1, n_rows - 1); tab_hline (t, TAL_2, 0, n_cols - 1, 1); tab_vline (t, TAL_2, 2, 0, n_rows - 1); @@ -205,14 +205,14 @@ 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)")); - tab_float (t, 2, 1, 0, c->intercept, 10, 2); + tab_double (t, 2, 1, 0, c->intercept, NULL); std_err = sqrt (gsl_matrix_get (c->cov, 0, 0)); - tab_float (t, 3, 1, 0, std_err, 10, 2); - tab_float (t, 4, 1, 0, 0.0, 10, 2); + tab_double (t, 3, 1, 0, std_err, NULL); + tab_double (t, 4, 1, 0, 0.0, NULL); t_stat = c->intercept / std_err; - tab_float (t, 5, 1, 0, t_stat, 10, 2); + tab_double (t, 5, 1, 0, t_stat, NULL); pval = 2 * gsl_cdf_tdist_Q (fabs (t_stat), 1.0); - tab_float (t, 6, 1, 0, pval, 10, 2); + tab_double (t, 6, 1, 0, pval, NULL); for (j = 0; j < c->n_coeffs; j++) { struct string tstr; @@ -240,32 +240,32 @@ reg_stats_coeff (pspp_linreg_cache * c) /* Regression coefficients. */ - tab_float (t, 2, this_row, 0, c->coeff[j]->estimate, 10, 2); + tab_double (t, 2, this_row, 0, c->coeff[j]->estimate, NULL); /* Standard error of the coefficients. */ std_err = sqrt (gsl_matrix_get (c->cov, j + 1, j + 1)); - tab_float (t, 3, this_row, 0, std_err, 10, 2); + tab_double (t, 3, this_row, 0, std_err, NULL); /* Standardized coefficient, i.e., regression coefficient if all variables had unit variance. */ beta = pspp_coeff_get_sd (c->coeff[j]); beta *= c->coeff[j]->estimate / c->depvar_std; - tab_float (t, 4, this_row, 0, beta, 10, 2); + tab_double (t, 4, this_row, 0, beta, NULL); /* Test statistic for H0: coefficient is 0. */ t_stat = c->coeff[j]->estimate / std_err; - tab_float (t, 5, this_row, 0, t_stat, 10, 2); + tab_double (t, 5, this_row, 0, t_stat, NULL); /* P values for the test statistic above. */ pval = 2 * gsl_cdf_tdist_Q (fabs (t_stat), (double) (c->n_obs - c->n_coeffs)); - tab_float (t, 6, this_row, 0, pval, 10, 2); + tab_double (t, 6, this_row, 0, pval, NULL); ds_destroy (&tstr); } tab_title (t, _("Coefficients")); @@ -290,7 +290,7 @@ reg_stats_anova (pspp_linreg_cache * c) assert (c != NULL); t = tab_create (n_cols, n_rows, 0); tab_headers (t, 2, 0, 1, 0); - tab_dim (t, tab_natural_dimensions); + tab_dim (t, tab_natural_dimensions, NULL); tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, n_cols - 1, n_rows - 1); @@ -309,23 +309,23 @@ reg_stats_anova (pspp_linreg_cache * c) tab_text (t, 1, 3, TAB_LEFT | TAT_TITLE, _("Total")); /* Sums of Squares */ - tab_float (t, 2, 1, 0, c->ssm, 10, 2); - tab_float (t, 2, 3, 0, c->sst, 10, 2); - tab_float (t, 2, 2, 0, c->sse, 10, 2); + tab_double (t, 2, 1, 0, c->ssm, NULL); + tab_double (t, 2, 3, 0, c->sst, NULL); + tab_double (t, 2, 2, 0, c->sse, NULL); /* Degrees of freedom */ - tab_text (t, 3, 1, TAB_RIGHT | TAT_PRINTF, "%g", c->dfm); - tab_text (t, 3, 2, TAB_RIGHT | TAT_PRINTF, "%g", c->dfe); - tab_text (t, 3, 3, TAB_RIGHT | TAT_PRINTF, "%g", c->dft); + tab_text_format (t, 3, 1, TAB_RIGHT, "%g", c->dfm); + tab_text_format (t, 3, 2, TAB_RIGHT, "%g", c->dfe); + tab_text_format (t, 3, 3, TAB_RIGHT, "%g", c->dft); /* Mean Squares */ - tab_float (t, 4, 1, TAB_RIGHT, msm, 8, 3); - tab_float (t, 4, 2, TAB_RIGHT, mse, 8, 3); + tab_double (t, 4, 1, TAB_RIGHT, msm, NULL); + tab_double (t, 4, 2, TAB_RIGHT, mse, NULL); - tab_float (t, 5, 1, 0, F, 8, 3); + tab_double (t, 5, 1, 0, F, NULL); - tab_float (t, 6, 1, 0, pval, 8, 3); + tab_double (t, 6, 1, 0, pval, NULL); tab_title (t, _("ANOVA")); tab_submit (t); @@ -381,7 +381,7 @@ reg_stats_bcov (pspp_linreg_cache * c) n_rows = 2 * (c->n_indeps + 1); t = tab_create (n_cols, n_rows, 0); tab_headers (t, 2, 0, 1, 0); - tab_dim (t, tab_natural_dimensions); + tab_dim (t, tab_natural_dimensions, NULL); tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, n_cols - 1, n_rows - 1); tab_hline (t, TAL_2, 0, n_cols - 1, 1); tab_vline (t, TAL_2, 2, 0, n_rows - 1); @@ -398,8 +398,8 @@ reg_stats_bcov (pspp_linreg_cache * c) { col = (i <= k) ? k : i; row = (i <= k) ? i : k; - tab_float (t, k + 2, i, TAB_CENTER, - gsl_matrix_get (c->cov, row, col), 8, 3); + tab_double (t, k + 2, i, TAB_CENTER, + gsl_matrix_get (c->cov, row, col), NULL); } } tab_title (t, _("Coefficient Correlations")); @@ -947,7 +947,7 @@ run_regression (struct casereader *input, struct cmd_regression *cmd, lopts.get_indep_mean_std[i] = 1; } models[k] = pspp_linreg_cache_alloc (dep_var, (const struct variable **) indep_vars, - X->m->size1, X->m->size2); + X->m->size1, n_indep); models[k]->depvar = dep_var; /* For large data sets, use QR decomposition.