/* PSPP - a program for statistical analysis.
- Copyright (C) 2005, 2009, 2010, 2011, 2012, 2013, 2014 Free Software Foundation, Inc.
+ Copyright (C) 2005, 2009, 2010, 2011, 2012, 2013, 2014, 2016 Free Software Foundation, Inc.
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
if (lex_match_id (lexer, "DEPENDENT"))
{
- if (!lex_force_match (lexer, T_EQUALS))
- goto error;
+ lex_match (lexer, T_EQUALS);
free (regression.dep_vars);
regression.n_dep_vars = 0;
}
else if (lex_match_id (lexer, "STATISTICS"))
{
+ unsigned long statistics = 0;
lex_match (lexer, T_EQUALS);
while (lex_token (lexer) != T_ENDCMD
{
if (lex_match (lexer, T_ALL))
{
- regression.stats = ~0;
+ statistics = ~0;
}
else if (lex_match_id (lexer, "DEFAULTS"))
{
- regression.stats |= STATS_DEFAULT;
+ statistics |= STATS_DEFAULT;
}
else if (lex_match_id (lexer, "R"))
{
- regression.stats |= STATS_R;
+ statistics |= STATS_R;
}
else if (lex_match_id (lexer, "COEFF"))
{
- regression.stats |= STATS_COEFF;
+ statistics |= STATS_COEFF;
}
else if (lex_match_id (lexer, "ANOVA"))
{
- regression.stats |= STATS_ANOVA;
+ statistics |= STATS_ANOVA;
}
else if (lex_match_id (lexer, "BCOV"))
{
- regression.stats |= STATS_BCOV;
+ statistics |= STATS_BCOV;
}
else if (lex_match_id (lexer, "CI"))
{
- regression.stats |= STATS_CI;
+ statistics |= STATS_CI;
- if (lex_match (lexer, T_LPAREN))
+ if (lex_match (lexer, T_LPAREN) &&
+ lex_force_num (lexer))
{
regression.ci = lex_number (lexer) / 100.0;
lex_get (lexer);
goto error;
}
}
+
+ if (statistics)
+ regression.stats = statistics;
+
}
else if (lex_match_id (lexer, "SAVE"))
{
workspace.pred_idx = -1;
workspace.writer = NULL;
workspace.reader = NULL;
+ workspace.residvars = NULL;
+ workspace.predvars = NULL;
if (save)
{
int i;
if (regression.resid)
{
- workspace.extras ++;
- workspace.res_idx = 0;
+ workspace.res_idx = workspace.extras ++;
workspace.residvars = xcalloc (regression.n_dep_vars, sizeof (*workspace.residvars));
for (i = 0; i < regression.n_dep_vars; ++i)
if (regression.pred)
{
- workspace.extras ++;
- workspace.pred_idx = 1;
+ workspace.pred_idx = workspace.extras ++;
workspace.predvars = xcalloc (regression.n_dep_vars, sizeof (*workspace.predvars));
for (i = 0; i < regression.n_dep_vars; ++i)
msg (SW, _("REGRESSION with SAVE ignores TEMPORARY. "
"Temporary transformations will be made permanent."));
+ if (dict_get_filter (dict))
+ msg (SW, _("REGRESSION with SAVE ignores FILTER. "
+ "All cases will be processed."));
+
workspace.writer = autopaging_writer_create (proto);
caseproto_unref (proto);
}
for (; (c = casereader_read (r)) != NULL; case_unref (c))
{
- struct ccase *outc = case_clone (c);
+ struct ccase *outc = case_create (casewriter_get_proto (ws->writer));
for (k = 0; k < cmd->n_dep_vars; k++)
{
const struct variable **vars = xnmalloc (cmd->n_vars, sizeof (*vars));
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_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_double (t, 1, 1, TAB_RIGHT, sqrt (rsq), NULL, RC_OTHER);
+ tab_double (t, 2, 1, TAB_RIGHT, rsq, NULL, RC_OTHER);
+ tab_double (t, 3, 1, TAB_RIGHT, adjrsq, NULL, RC_OTHER);
+ tab_double (t, 4, 1, TAB_RIGHT, std_error, NULL, RC_OTHER);
tab_title (t, _("Model Summary (%s)"), var_to_string (var));
tab_submit (t);
}
tab_text (t, 5, 1, TAB_CENTER | TAT_TITLE, _("t"));
tab_text (t, 6, 1, TAB_CENTER | TAT_TITLE, _("Sig."));
tab_text (t, 1, heading_rows, TAB_LEFT | TAT_TITLE, _("(Constant)"));
- tab_double (t, 2, heading_rows, 0, linreg_intercept (c), NULL);
+ tab_double (t, 2, heading_rows, 0, linreg_intercept (c), NULL, RC_OTHER);
std_err = sqrt (gsl_matrix_get (linreg_cov (c), 0, 0));
if (cmd->stats & STATS_CI)
{
double lower = linreg_intercept (c) - tval * std_err ;
double upper = linreg_intercept (c) + tval * std_err ;
- tab_double (t, 7, heading_rows, 0, lower, NULL);
- tab_double (t, 8, heading_rows, 0, upper, NULL);
+ tab_double (t, 7, heading_rows, 0, lower, NULL, RC_OTHER);
+ tab_double (t, 8, heading_rows, 0, upper, NULL, RC_OTHER);
tab_joint_text_format (t, 7, 0, 8, 0, TAB_CENTER | TAT_TITLE, _("%g%% Confidence Interval for B"), cmd->ci * 100);
tab_hline (t, TAL_1, 7, 8, 1);
tab_text (t, 7, 1, TAB_CENTER | TAT_TITLE, _("Lower Bound"));
tab_text (t, 8, 1, TAB_CENTER | TAT_TITLE, _("Upper Bound"));
}
- tab_double (t, 3, heading_rows, 0, std_err, NULL);
- tab_double (t, 4, heading_rows, 0, 0.0, NULL);
+ tab_double (t, 3, heading_rows, 0, std_err, NULL, RC_OTHER);
+ tab_double (t, 4, heading_rows, 0, 0.0, NULL, RC_OTHER);
t_stat = linreg_intercept (c) / std_err;
- tab_double (t, 5, heading_rows, 0, t_stat, NULL);
+ tab_double (t, 5, heading_rows, 0, t_stat, NULL, RC_OTHER);
pval =
2 * gsl_cdf_tdist_Q (fabs (t_stat),
(double) (linreg_n_obs (c) - linreg_n_coeffs (c)));
- tab_double (t, 6, heading_rows, 0, pval, NULL);
+ tab_double (t, 6, heading_rows, 0, pval, NULL, RC_PVALUE);
for (j = 0; j < linreg_n_coeffs (c); j++)
{
/*
Regression coefficients.
*/
- tab_double (t, 2, this_row, 0, linreg_coeff (c, j), NULL);
+ tab_double (t, 2, this_row, 0, linreg_coeff (c, j), NULL, RC_OTHER);
/*
Standard error of the coefficients.
*/
std_err = sqrt (gsl_matrix_get (linreg_cov (c), j + 1, j + 1));
- tab_double (t, 3, this_row, 0, std_err, NULL);
+ tab_double (t, 3, this_row, 0, std_err, NULL, RC_OTHER);
/*
Standardized coefficient, i.e., regression coefficient
if all variables had unit variance.
beta = sqrt (gsl_matrix_get (cov, j, j));
beta *= linreg_coeff (c, j) /
sqrt (gsl_matrix_get (cov, cov->size1 - 1, cov->size2 - 1));
- tab_double (t, 4, this_row, 0, beta, NULL);
+ tab_double (t, 4, this_row, 0, beta, NULL, RC_OTHER);
/*
Test statistic for H0: coefficient is 0.
*/
t_stat = linreg_coeff (c, j) / std_err;
- tab_double (t, 5, this_row, 0, t_stat, NULL);
+ tab_double (t, 5, this_row, 0, t_stat, NULL, RC_OTHER);
/*
P values for the test statistic above.
*/
pval = 2 * gsl_cdf_tdist_Q (fabs (t_stat), df);
- tab_double (t, 6, this_row, 0, pval, NULL);
+ tab_double (t, 6, this_row, 0, pval, NULL, RC_PVALUE);
ds_destroy (&tstr);
if (cmd->stats & STATS_CI)
double lower = linreg_coeff (c, j) - tval * std_err ;
double upper = linreg_coeff (c, j) + tval * std_err ;
- tab_double (t, 7, this_row, 0, lower, NULL);
- tab_double (t, 8, this_row, 0, upper, NULL);
+ tab_double (t, 7, this_row, 0, lower, NULL, RC_OTHER);
+ tab_double (t, 8, this_row, 0, upper, NULL, RC_OTHER);
}
}
tab_title (t, _("Coefficients (%s)"), var_to_string (var));
tab_text (t, 1, 3, TAB_LEFT | TAT_TITLE, _("Total"));
/* Sums of Squares */
- tab_double (t, 2, 1, 0, linreg_ssreg (c), NULL);
- tab_double (t, 2, 3, 0, linreg_sst (c), NULL);
- tab_double (t, 2, 2, 0, linreg_sse (c), NULL);
+ tab_double (t, 2, 1, 0, linreg_ssreg (c), NULL, RC_OTHER);
+ tab_double (t, 2, 3, 0, linreg_sst (c), NULL, RC_OTHER);
+ tab_double (t, 2, 2, 0, linreg_sse (c), NULL, RC_OTHER);
/* Degrees of freedom */
tab_text_format (t, 3, 3, TAB_RIGHT, "%.*g", DBL_DIG + 1, c->dft);
/* Mean Squares */
- tab_double (t, 4, 1, TAB_RIGHT, msm, NULL);
- tab_double (t, 4, 2, TAB_RIGHT, mse, NULL);
+ tab_double (t, 4, 1, TAB_RIGHT, msm, NULL, RC_OTHER);
+ tab_double (t, 4, 2, TAB_RIGHT, mse, NULL, RC_OTHER);
- tab_double (t, 5, 1, 0, F, NULL);
+ tab_double (t, 5, 1, 0, F, NULL, RC_OTHER);
- tab_double (t, 6, 1, 0, pval, NULL);
+ tab_double (t, 6, 1, 0, pval, NULL, RC_PVALUE);
tab_title (t, _("ANOVA (%s)"), var_to_string (var));
tab_submit (t);
col = (i <= k) ? k : i;
row = (i <= k) ? i : k;
tab_double (t, k + 2, i, TAB_CENTER,
- gsl_matrix_get (c->cov, row, col), NULL);
+ gsl_matrix_get (c->cov, row, col), NULL, RC_OTHER);
}
}
tab_title (t, _("Coefficient Correlations (%s)"), var_to_string (var));
projects / pspp / blobdiff