/* The weight variable */
const struct variable *wv;
- /*
- Sums of squares due to different variables. Element 0 is the SSE
- for the entire model. For i > 0, element i is the SS due to
- variable i.
- */
- gsl_vector * ssq;
-
bool intercept;
};
{
double total_ssq;
struct moments *totals;
+
+ struct categoricals *cats;
+
+ /*
+ Sums of squares due to different variables. Element 0 is the SSE
+ for the entire model. For i > 0, element i is the SS due to
+ variable i.
+ */
+ gsl_vector *ssq;
};
-static void output_glm (struct glm_spec *, const struct glm_workspace *ws);
-static void run_glm (struct glm_spec *cmd, struct casereader *input, const struct dataset *ds);
+static void output_glm (const struct glm_spec *,
+ const struct glm_workspace *ws);
+static void run_glm (struct glm_spec *cmd, struct casereader *input,
+ const struct dataset *ds);
int
cmd_glm (struct lexer *lexer, struct dataset *ds)
{
- const struct dictionary *dict = dataset_dict (ds);
- struct glm_spec glm ;
+ struct const_var_set *factors = NULL;
+ const struct dictionary *dict = dataset_dict (ds);
+ struct glm_spec glm;
glm.n_dep_vars = 0;
glm.n_factor_vars = 0;
glm.dep_vars = NULL;
glm.intercept = true;
glm.wv = dict_get_weight (dict);
-
+
if (!parse_variables_const (lexer, dict,
&glm.dep_vars, &glm.n_dep_vars,
PV_NO_DUPLICATE | PV_NUMERIC))
PV_NO_DUPLICATE | PV_NUMERIC))
goto error;
- if ( glm.n_dep_vars > 1)
+ if (glm.n_dep_vars > 1)
{
msg (ME, _("Multivariate analysis is not yet implemented"));
return CMD_FAILURE;
}
- struct const_var_set *factors = const_var_set_create_from_array (glm.factor_vars, glm.n_factor_vars);
-
+ factors =
+ const_var_set_create_from_array (glm.factor_vars, glm.n_factor_vars);
while (lex_token (lexer) != T_ENDCMD)
{
lex_match (lexer, T_SLASH);
if (lex_match_id (lexer, "MISSING"))
- {
- lex_match (lexer, T_EQUALS);
- while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
- {
+ {
+ lex_match (lexer, T_EQUALS);
+ while (lex_token (lexer) != T_ENDCMD
+ && lex_token (lexer) != T_SLASH)
+ {
if (lex_match_id (lexer, "INCLUDE"))
{
glm.exclude = MV_SYSTEM;
}
else
{
- lex_error (lexer, NULL);
+ lex_error (lexer, NULL);
goto error;
}
}
}
else if (lex_match_id (lexer, "INTERCEPT"))
- {
- lex_match (lexer, T_EQUALS);
- while (lex_token (lexer) != T_ENDCMD && lex_token (lexer) != T_SLASH)
- {
+ {
+ lex_match (lexer, T_EQUALS);
+ while (lex_token (lexer) != T_ENDCMD
+ && lex_token (lexer) != T_SLASH)
+ {
if (lex_match_id (lexer, "INCLUDE"))
{
glm.intercept = true;
}
else
{
- lex_error (lexer, NULL);
+ lex_error (lexer, NULL);
goto error;
}
}
}
+#if 0
else if (lex_match_id (lexer, "DESIGN"))
- {
+ {
size_t n_des;
const struct variable **des;
- lex_match (lexer, T_EQUALS);
+ lex_match (lexer, T_EQUALS);
parse_const_var_set_vars (lexer, factors, &des, &n_des, 0);
}
+#endif
else
{
lex_error (lexer, NULL);
ok = proc_commit (ds) && ok;
}
+ const_var_set_destroy (factors);
+ free (glm.factor_vars);
+ free (glm.dep_vars);
+
return CMD_SUCCESS;
- error:
+error:
+
+ const_var_set_destroy (factors);
+ free (glm.factor_vars);
+ free (glm.dep_vars);
+
return CMD_FAILURE;
}
-static void get_ssq (struct covariance *, gsl_vector *, struct glm_spec *);
+static void get_ssq (struct covariance *, gsl_vector *,
+ const struct glm_spec *);
static bool
not_dropped (size_t j, size_t * dropped, size_t n_dropped)
for (i = 0; i < n_dropped; i++)
{
- if (j == dropped [i])
+ if (j == dropped[i])
return false;
}
return true;
}
static void
-get_ssq (struct covariance * cov, gsl_vector * ssq, struct glm_spec * cmd)
+get_ssq (struct covariance *cov, gsl_vector * ssq, const struct glm_spec *cmd)
{
const struct variable **vars;
- gsl_matrix * small_cov = NULL;
- gsl_matrix * cm = covariance_calculate_unnormalized (cov);
+ gsl_matrix *small_cov = NULL;
+ gsl_matrix *cm = covariance_calculate_unnormalized (cov);
size_t i;
size_t j;
size_t k;
size_t n;
size_t m;
- size_t * dropped;
+ size_t *dropped;
size_t n_dropped;
dropped = xcalloc (covariance_dim (cov), sizeof (*dropped));
n_dropped = 0;
for (i = 1; i < covariance_dim (cov); i++)
{
- if (vars [i] == cmd->factor_vars [k])
+ if (vars[i] == cmd->factor_vars[k])
{
- dropped [n_dropped++] = i;
+ dropped[n_dropped++] = i;
}
}
- small_cov = gsl_matrix_alloc (cm->size1 - n_dropped, cm->size2 - n_dropped);
+ small_cov =
+ gsl_matrix_alloc (cm->size1 - n_dropped, cm->size2 - n_dropped);
gsl_matrix_set (small_cov, 0, 0, gsl_matrix_get (cm, 0, 0));
n = 0;
m = 0;
{
if (not_dropped (j, dropped, n_dropped))
{
- gsl_matrix_set (small_cov, n, m, gsl_matrix_get (cm, i, j));
+ gsl_matrix_set (small_cov, n, m,
+ gsl_matrix_get (cm, i, j));
m++;
}
}
}
}
reg_sweep (small_cov, 0);
- gsl_vector_set (ssq, k + 1,
+ gsl_vector_set (ssq, k + 1,
gsl_matrix_get (small_cov, 0, 0)
- gsl_vector_get (ssq, 0));
gsl_matrix_free (small_cov);
free (dropped);
free (vars);
gsl_matrix_free (cm);
-
}
-static void dump_matrix (const gsl_matrix *m);
+//static void dump_matrix (const gsl_matrix *m);
static void
-run_glm (struct glm_spec *cmd, struct casereader *input, const struct dataset *ds)
+run_glm (struct glm_spec *cmd, struct casereader *input,
+ const struct dataset *ds)
{
+ bool warn_bad_weight = true;
int v;
struct taint *taint;
struct dictionary *dict = dataset_dict (ds);
struct ccase *c;
struct glm_workspace ws;
+ struct covariance *cov;
+ ws.cats = categoricals_create (cmd->factor_vars, cmd->n_factor_vars,
+ cmd->wv, cmd->exclude,
+ NULL, NULL, NULL, NULL);
- struct categoricals *cats = categoricals_create (cmd->factor_vars, cmd->n_factor_vars,
- cmd->wv, cmd->exclude,
- NULL, NULL,
- NULL, NULL);
-
- struct covariance *cov = covariance_2pass_create (cmd->n_dep_vars, cmd->dep_vars,
- cats,
- cmd->wv, cmd->exclude);
+ cov = covariance_2pass_create (cmd->n_dep_vars, cmd->dep_vars,
+ ws.cats, cmd->wv, cmd->exclude);
c = casereader_peek (input, 0);
ws.totals = moments_create (MOMENT_VARIANCE);
- bool warn_bad_weight = true;
for (reader = casereader_clone (input);
(c = casereader_read (reader)) != NULL; case_unref (c))
{
double weight = dict_get_case_weight (dict, c, &warn_bad_weight);
- for ( v = 0; v < cmd->n_dep_vars; ++v)
- moments_pass_one (ws.totals, case_data (c, cmd->dep_vars[v])->f, weight);
+ for (v = 0; v < cmd->n_dep_vars; ++v)
+ moments_pass_one (ws.totals, case_data (c, cmd->dep_vars[v])->f,
+ weight);
covariance_accumulate_pass1 (cov, c);
}
casereader_destroy (reader);
- categoricals_done (cats);
+ categoricals_done (ws.cats);
- for (reader = casereader_clone (input);
+ for (reader = input;
(c = casereader_read (reader)) != NULL; case_unref (c))
{
double weight = dict_get_case_weight (dict, c, &warn_bad_weight);
- for ( v = 0; v < cmd->n_dep_vars; ++v)
- moments_pass_two (ws.totals, case_data (c, cmd->dep_vars[v])->f, weight);
+ for (v = 0; v < cmd->n_dep_vars; ++v)
+ moments_pass_two (ws.totals, case_data (c, cmd->dep_vars[v])->f,
+ weight);
covariance_accumulate_pass2 (cov, c);
}
{
gsl_matrix *cm = covariance_calculate_unnormalized (cov);
- dump_matrix (cm);
+ // dump_matrix (cm);
ws.total_ssq = gsl_matrix_get (cm, 0, 0);
reg_sweep (cm, 0);
/*
- Store the overall SSE.
+ Store the overall SSE.
*/
- cmd->ssq = gsl_vector_alloc (cm->size1);
- gsl_vector_set (cmd->ssq, 0, gsl_matrix_get (cm, 0, 0));
- get_ssq (cov, cmd->ssq, cmd);
-
- gsl_vector_free (cmd->ssq);
- dump_matrix (cm);
+ ws.ssq = gsl_vector_alloc (cm->size1);
+ gsl_vector_set (ws.ssq, 0, gsl_matrix_get (cm, 0, 0));
+ get_ssq (cov, ws.ssq, cmd);
+ // dump_matrix (cm);
gsl_matrix_free (cm);
}
if (!taint_has_tainted_successor (taint))
output_glm (cmd, &ws);
+ gsl_vector_free (ws.ssq);
+
+ covariance_destroy (cov);
+ moments_destroy (ws.totals);
+
taint_destroy (taint);
}
static void
-output_glm (struct glm_spec *cmd, const struct glm_workspace *ws)
+output_glm (const struct glm_spec *cmd, const struct glm_workspace *ws)
{
- const struct fmt_spec *wfmt = cmd->wv ? var_get_print_format (cmd->wv) : &F_8_0;
+ const struct fmt_spec *wfmt =
+ cmd->wv ? var_get_print_format (cmd->wv) : &F_8_0;
+
+ double n_total, mean;
+ double df_corr = 0.0;
+ double mse = 0;
int f;
int r;
const int heading_columns = 1;
const int heading_rows = 1;
- struct tab_table *t ;
+ struct tab_table *t;
const int nc = 6;
int nr = heading_rows + 4 + cmd->n_factor_vars;
tab_headers (t, heading_columns, 0, heading_rows, 0);
- tab_box (t,
- TAL_2, TAL_2,
- -1, TAL_1,
- 0, 0,
- nc - 1, nr - 1);
+ tab_box (t, TAL_2, TAL_2, -1, TAL_1, 0, 0, nc - 1, nr - 1);
tab_hline (t, TAL_2, 0, nc - 1, heading_rows);
tab_vline (t, TAL_2, heading_columns, 0, nr - 1);
tab_text (t, 0, 0, TAB_CENTER | TAT_TITLE, _("Source"));
/* TRANSLATORS: The parameter is a roman numeral */
- tab_text_format (t, 1, 0, TAB_CENTER | TAT_TITLE, _("Type %s Sum of Squares"), "III");
+ tab_text_format (t, 1, 0, TAB_CENTER | TAT_TITLE,
+ _("Type %s Sum of Squares"), "III");
tab_text (t, 2, 0, TAB_CENTER | TAT_TITLE, _("df"));
tab_text (t, 3, 0, TAB_CENTER | TAT_TITLE, _("Mean Square"));
tab_text (t, 4, 0, TAB_CENTER | TAT_TITLE, _("F"));
tab_text (t, 5, 0, TAB_CENTER | TAT_TITLE, _("Sig."));
+ moments_calculate (ws->totals, &n_total, &mean, NULL, NULL, NULL);
+
+ if (cmd->intercept)
+ df_corr += 1.0;
+
+ for (f = 0; f < cmd->n_factor_vars; ++f)
+ df_corr += categoricals_n_count (ws->cats, f) - 1.0;
+
+ mse = gsl_vector_get (ws->ssq, 0) / (n_total - df_corr);
+
r = heading_rows;
- tab_text (t, 0, r++, TAB_LEFT | TAT_TITLE, _("Corrected Model"));
+ tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Corrected Model"));
+
+ r++;
- double intercept, n_total;
if (cmd->intercept)
{
- double mean;
- moments_calculate (ws->totals, &n_total, &mean, NULL, NULL, NULL);
- intercept = pow2 (mean * n_total) / n_total;
-
+ const double intercept = pow2 (mean * n_total) / n_total;
+ const double df = 1.0;
+ const double F = intercept / df / mse;
tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Intercept"));
tab_double (t, 1, r, 0, intercept, NULL);
tab_double (t, 2, r, 0, 1.00, wfmt);
-
- tab_double (t, 3, r, 0, intercept / 1.0 , NULL);
+ tab_double (t, 3, r, 0, intercept / df, NULL);
+ tab_double (t, 4, r, 0, F, NULL);
+ tab_double (t, 5, r, 0, gsl_cdf_fdist_Q (F, df, n_total - df_corr),
+ NULL);
r++;
}
for (f = 0; f < cmd->n_factor_vars; ++f)
{
- tab_text (t, 0, r++, TAB_LEFT | TAT_TITLE,
+ const double df = categoricals_n_count (ws->cats, f) - 1.0;
+ const double ssq = gsl_vector_get (ws->ssq, f + 1);
+ const double F = ssq / df / mse;
+ tab_text (t, 0, r, TAB_LEFT | TAT_TITLE,
var_to_string (cmd->factor_vars[f]));
+
+ tab_double (t, 1, r, 0, ssq, NULL);
+ tab_double (t, 2, r, 0, df, wfmt);
+ tab_double (t, 3, r, 0, ssq / df, NULL);
+ tab_double (t, 4, r, 0, F, NULL);
+
+ tab_double (t, 5, r, 0, gsl_cdf_fdist_Q (F, df, n_total - df_corr),
+ NULL);
+
+
+ r++;
}
- tab_text (t, 0, r++, TAB_LEFT | TAT_TITLE, _("Error"));
+ {
+ /* Corrected Model */
+ const double df = df_corr - 1.0;
+ const double ssq = ws->total_ssq - gsl_vector_get (ws->ssq, 0);
+ const double F = ssq / df / mse;
+ tab_double (t, 1, heading_rows, 0, ssq, NULL);
+ tab_double (t, 2, heading_rows, 0, df, wfmt);
+ tab_double (t, 3, heading_rows, 0, ssq / df, NULL);
+ tab_double (t, 4, heading_rows, 0, F, NULL);
+
+ tab_double (t, 5, heading_rows, 0,
+ gsl_cdf_fdist_Q (F, df, n_total - df_corr), NULL);
+ }
+
+ {
+ const double df = n_total - df_corr;
+ const double ssq = gsl_vector_get (ws->ssq, 0);
+ const double mse = ssq / df;
+ tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Error"));
+ tab_double (t, 1, r, 0, ssq, NULL);
+ tab_double (t, 2, r, 0, df, wfmt);
+ tab_double (t, 3, r++, 0, mse, NULL);
+ }
if (cmd->intercept)
{
- double ssq = intercept + ws->total_ssq;
- double mse = ssq / n_total;
+ const double intercept = pow2 (mean * n_total) / n_total;
+ const double ssq = intercept + ws->total_ssq;
+
tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Total"));
tab_double (t, 1, r, 0, ssq, NULL);
tab_double (t, 2, r, 0, n_total, wfmt);
tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Corrected Total"));
+
tab_double (t, 1, r, 0, ws->total_ssq, NULL);
tab_double (t, 2, r, 0, n_total - 1.0, wfmt);
tab_submit (t);
}
-static
-void dump_matrix (const gsl_matrix *m)
+#if 0
+static void
+dump_matrix (const gsl_matrix * m)
{
size_t i, j;
for (i = 0; i < m->size1; ++i)
}
printf ("\n");
}
+#endif
projects / pspp-builds.git / commitdiff