#include "math/covariance.h"
#include "math/interaction.h"
#include "math/moments.h"
-#include "output/tab.h"
+#include "output/pivot-table.h"
#include "gettext.h"
+#define N_(msgid) msgid
#define _(msgid) gettext (msgid)
struct glm_spec
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.
PV_NO_DUPLICATE | PV_NUMERIC))
goto error;
- lex_force_match (lexer, T_BY);
+ if (! lex_force_match (lexer, T_BY))
+ goto error;
if (!parse_variables_const (lexer, glm.dict,
&glm.factor_vars, &glm.n_factor_vars,
lex_error (lexer, NULL);
goto error;
}
-
+
glm.alpha = lex_number (lexer);
lex_get (lexer);
- if ( ! lex_force_match (lexer, T_RPAREN))
+ if (! lex_force_match (lexer, T_RPAREN))
{
lex_error (lexer, NULL);
goto error;
else if (lex_match_id (lexer, "METHOD"))
{
lex_match (lexer, T_EQUALS);
- if ( !lex_force_match_id (lexer, "SSTYPE"))
+ if (!lex_force_match_id (lexer, "SSTYPE"))
{
lex_error (lexer, NULL);
goto error;
}
- if ( ! lex_force_match (lexer, T_LPAREN))
+ if (! lex_force_match (lexer, T_LPAREN))
{
lex_error (lexer, NULL);
goto error;
}
- if ( ! lex_force_int (lexer))
+ if (!lex_force_int_range (lexer, "SSTYPE", 1, 3))
{
lex_error (lexer, NULL);
goto error;
}
glm.ss_type = lex_integer (lexer);
- if (1 > glm.ss_type && 3 < glm.ss_type )
- {
- msg (ME, _("Only types 1, 2 & 3 sums of squares are currently implemented"));
- goto error;
- }
-
lex_get (lexer);
- if ( ! lex_force_match (lexer, T_RPAREN))
+ if (! lex_force_match (lexer, T_RPAREN))
{
lex_error (lexer, NULL);
goto error;
}
}
- if ( ! design )
+ if (! design)
{
design_full (&glm);
}
const_var_set_destroy (factors);
free (glm.factor_vars);
+ for (i = 0 ; i < glm.n_interactions; ++i)
+ interaction_destroy (glm.interactions[i]);
+
free (glm.interactions);
free (glm.dep_vars);
size_t j;
size_t n = 0;
size_t m = 0;
-
+
for (i = 0; i < cov->size1; i++)
{
if (not_dropped (i, dropped_f))
- {
+ {
m = 0;
for (j = 0; j < cov->size2; j++)
{
gsl_matrix_set (submatrix, n, m,
gsl_matrix_get (cov, i, j));
m++;
- }
+ }
}
n++;
}
}
-/*
+/*
Type 1 sums of squares.
Populate SSQ with the Type 1 sums of squares according to COV
*/
static void
ssq_type1 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
{
- gsl_matrix *cm = covariance_calculate_unnormalized (cov);
+ const gsl_matrix *cm = covariance_calculate_unnormalized (cov);
size_t i;
size_t k;
- bool *model_dropped = xcalloc (covariance_dim (cov), sizeof (*model_dropped));
- bool *submodel_dropped = xcalloc (covariance_dim (cov), sizeof (*submodel_dropped));
+ bool *model_dropped = XCALLOC (covariance_dim (cov), bool);
+ bool *submodel_dropped = XCALLOC (covariance_dim (cov), bool);
const struct categoricals *cats = covariance_get_categoricals (cov);
size_t n_dropped_model = 0;
{
gsl_matrix *model_cov = NULL;
gsl_matrix *submodel_cov = NULL;
-
+
n_dropped_submodel = n_dropped_model;
for (i = cmd->n_dep_vars; i < covariance_dim (cov); i++)
{
for (i = cmd->n_dep_vars; i < covariance_dim (cov); i++)
{
- const struct interaction * x =
+ const struct interaction * x =
categoricals_get_interaction_by_subscript (cats, i - cmd->n_dep_vars);
- if ( x == cmd->interactions [k])
+ if (x == cmd->interactions [k])
{
model_dropped[i] = false;
n_dropped_model--;
gsl_vector_set (ssq, k + 1,
gsl_matrix_get (submodel_cov, 0, 0) - gsl_matrix_get (model_cov, 0, 0)
- );
+ );
gsl_matrix_free (model_cov);
gsl_matrix_free (submodel_cov);
free (model_dropped);
free (submodel_dropped);
- gsl_matrix_free (cm);
}
-/*
+/*
Type 2 sums of squares.
Populate SSQ with the Type 2 sums of squares according to COV
*/
static void
ssq_type2 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
{
- gsl_matrix *cm = covariance_calculate_unnormalized (cov);
+ const gsl_matrix *cm = covariance_calculate_unnormalized (cov);
size_t i;
size_t k;
- bool *model_dropped = xcalloc (covariance_dim (cov), sizeof (*model_dropped));
- bool *submodel_dropped = xcalloc (covariance_dim (cov), sizeof (*submodel_dropped));
+ bool *model_dropped = XCALLOC (covariance_dim (cov), bool);
+ bool *submodel_dropped = XCALLOC (covariance_dim (cov), bool);
const struct categoricals *cats = covariance_get_categoricals (cov);
for (k = 0; k < cmd->n_interactions; k++)
size_t n_dropped_submodel = 0;
for (i = cmd->n_dep_vars; i < covariance_dim (cov); i++)
{
- const struct interaction * x =
+ const struct interaction * x =
categoricals_get_interaction_by_subscript (cats, i - cmd->n_dep_vars);
model_dropped[i] = false;
n_dropped_submodel++;
submodel_dropped[i] = true;
- if ( cmd->interactions [k]->n_vars < x->n_vars)
+ if (cmd->interactions [k]->n_vars < x->n_vars)
{
assert (n_dropped_model < covariance_dim (cov));
n_dropped_model++;
gsl_vector_set (ssq, k + 1,
gsl_matrix_get (submodel_cov, 0, 0) - gsl_matrix_get (model_cov, 0, 0)
- );
+ );
gsl_matrix_free (model_cov);
gsl_matrix_free (submodel_cov);
free (model_dropped);
free (submodel_dropped);
- gsl_matrix_free (cm);
}
-/*
+/*
Type 3 sums of squares.
Populate SSQ with the Type 2 sums of squares according to COV
*/
static void
ssq_type3 (struct covariance *cov, gsl_vector *ssq, const struct glm_spec *cmd)
{
- gsl_matrix *cm = covariance_calculate_unnormalized (cov);
+ const gsl_matrix *cm = covariance_calculate_unnormalized (cov);
size_t i;
size_t k;
- bool *model_dropped = xcalloc (covariance_dim (cov), sizeof (*model_dropped));
- bool *submodel_dropped = xcalloc (covariance_dim (cov), sizeof (*submodel_dropped));
+ bool *model_dropped = XCALLOC (covariance_dim (cov), bool);
+ bool *submodel_dropped = XCALLOC (covariance_dim (cov), bool);
const struct categoricals *cats = covariance_get_categoricals (cov);
double ss0;
for (i = cmd->n_dep_vars; i < covariance_dim (cov); i++)
{
- const struct interaction * x =
+ const struct interaction * x =
categoricals_get_interaction_by_subscript (cats, i - cmd->n_dep_vars);
model_dropped[i] = false;
- if ( cmd->interactions [k] == x)
+ if (cmd->interactions [k] == x)
{
assert (n_dropped_model < covariance_dim (cov));
n_dropped_model++;
gsl_matrix_free (model_cov);
}
free (model_dropped);
-
- gsl_matrix_free (cm);
}
struct glm_workspace ws;
struct covariance *cov;
+ input = casereader_create_filter_missing (input,
+ cmd->dep_vars, cmd->n_dep_vars,
+ cmd->exclude,
+ NULL, NULL);
+
+ input = casereader_create_filter_missing (input,
+ cmd->factor_vars, cmd->n_factor_vars,
+ cmd->exclude,
+ NULL, NULL);
+
ws.cats = categoricals_create (cmd->interactions, cmd->n_interactions,
- cmd->wv, cmd->exclude, MV_ANY);
+ cmd->wv, MV_ANY);
cov = covariance_2pass_create (cmd->n_dep_vars, cmd->dep_vars,
- ws.cats, cmd->wv, cmd->exclude);
+ ws.cats, cmd->wv, cmd->exclude, true);
c = casereader_peek (input, 0);
if (cmd->dump_coding)
{
- struct tab_table *t =
- covariance_dump_enc_header (cov,
- 1 + casereader_count_cases (input));
+ struct pivot_table *t = covariance_dump_enc_header (cov);
for (reader = input;
(c = casereader_read (reader)) != NULL; case_unref (c))
{
covariance_dump_enc (cov, c, t);
}
- casereader_destroy (reader);
- tab_submit (t);
+
+ pivot_table_submit (t);
}
{
- gsl_matrix *cm = covariance_calculate_unnormalized (cov);
+ const gsl_matrix *ucm = covariance_calculate_unnormalized (cov);
+ gsl_matrix *cm = gsl_matrix_alloc (ucm->size1, ucm->size2);
+ gsl_matrix_memcpy (cm, ucm);
// dump_matrix (cm);
break;
}
// dump_matrix (cm);
-
gsl_matrix_free (cm);
}
taint_destroy (taint);
}
-static const char *roman[] =
- {
- "", /* The Romans had no concept of zero */
- "I",
- "II",
- "III",
- "IV"
- };
+static void
+put_glm_row (struct pivot_table *table, int row,
+ double a, double b, double c, double d, double e)
+{
+ double entries[] = { a, b, c, d, e };
+
+ for (size_t col = 0; col < sizeof entries / sizeof *entries; col++)
+ if (entries[col] != SYSMIS)
+ pivot_table_put2 (table, col, row,
+ pivot_value_new_number (entries[col]));
+}
static void
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;
+ struct pivot_table *table = pivot_table_create (
+ N_("Tests of Between-Subjects Effects"));
+
+ pivot_dimension_create (table, PIVOT_AXIS_COLUMN, N_("Statistics"),
+ (cmd->ss_type == 1 ? N_("Type I Sum Of Squares")
+ : cmd->ss_type == 2 ? N_("Type II Sum Of Squares")
+ : N_("Type III Sum Of Squares")), PIVOT_RC_OTHER,
+ N_("df"), PIVOT_RC_COUNT,
+ N_("Mean Square"), PIVOT_RC_OTHER,
+ N_("F"), PIVOT_RC_OTHER,
+ N_("Sig."), PIVOT_RC_SIGNIFICANCE);
+
+ struct pivot_dimension *source = pivot_dimension_create (
+ table, PIVOT_AXIS_ROW, N_("Source"),
+ cmd->intercept ? N_("Corrected Model") : N_("Model"));
- double intercept_ssq;
- double ssq_effects;
double n_total, mean;
- double df_corr = 1.0;
- double mse = 0;
-
- int f;
- int r;
- const int heading_columns = 1;
- const int heading_rows = 1;
- struct tab_table *t;
-
- const int nc = 6;
- int nr = heading_rows + 3 + cmd->n_interactions;
- if (cmd->intercept)
- nr += 2;
-
- msg (MW, "GLM is experimental. Do not rely on these results.");
- t = tab_create (nc, nr);
- tab_title (t, _("Tests of Between-Subjects Effects"));
-
- 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_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"),
- roman[cmd->ss_type]);
- 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);
- df_corr += categoricals_df_total (ws->cats);
-
- r = heading_rows;
- if (cmd->intercept)
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Corrected Model"));
- else
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Model"));
-
- r++;
-
- mse = gsl_vector_get (ws->ssq, 0) / (n_total - df_corr);
+ double df_corr = 1.0 + categoricals_df_total (ws->cats);
- intercept_ssq = pow2 (mean * n_total) / n_total;
-
- ssq_effects = 0.0;
+ double mse = gsl_vector_get (ws->ssq, 0) / (n_total - df_corr);
+ double intercept_ssq = pow2 (mean * n_total) / n_total;
if (cmd->intercept)
{
- const double df = 1.0;
- const double F = intercept_ssq / df / mse;
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Intercept"));
- tab_double (t, 1, r, 0, intercept_ssq, NULL);
- tab_double (t, 2, r, 0, 1.00, wfmt);
- tab_double (t, 3, r, 0, intercept_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++;
+ int row = pivot_category_create_leaf (
+ source->root, pivot_value_new_text (N_("Intercept")));
+
+ /* The intercept for unbalanced models is of limited use and
+ nobody knows how to calculate it properly */
+ if (categoricals_isbalanced (ws->cats))
+ {
+ const double df = 1.0;
+ const double F = intercept_ssq / df / mse;
+ put_glm_row (table, row, intercept_ssq, 1.0, intercept_ssq / df,
+ F, gsl_cdf_fdist_Q (F, df, n_total - df_corr));
+ }
}
- for (f = 0; f < cmd->n_interactions; ++f)
+ double ssq_effects = 0.0;
+ for (int f = 0; f < cmd->n_interactions; ++f)
{
- struct string str = DS_EMPTY_INITIALIZER;
double df = categoricals_df (ws->cats, f);
-
double ssq = gsl_vector_get (ws->ssq, f + 1);
- double F;
-
ssq_effects += ssq;
-
- if (! cmd->intercept)
+ if (!cmd->intercept)
{
df++;
ssq += intercept_ssq;
}
+ double F = ssq / df / mse;
- F = ssq / df / mse;
+ struct string str = DS_EMPTY_INITIALIZER;
interaction_to_string (cmd->interactions[f], &str);
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, ds_cstr (&str));
- ds_destroy (&str);
-
- 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);
+ int row = pivot_category_create_leaf (
+ source->root, pivot_value_new_user_text_nocopy (ds_steal_cstr (&str)));
- tab_double (t, 5, r, 0, gsl_cdf_fdist_Q (F, df, n_total - df_corr),
- NULL);
- r++;
+ put_glm_row (table, row, ssq, df, ssq / df, F,
+ gsl_cdf_fdist_Q (F, df, n_total - df_corr));
}
{
/* Model / Corrected Model */
double df = df_corr;
double ssq = ws->total_ssq - gsl_vector_get (ws->ssq, 0);
- double F;
-
- if ( cmd->intercept )
- df --;
+ if (cmd->intercept)
+ df--;
else
ssq += intercept_ssq;
-
- 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);
+ double F = ssq / df / mse;
+ put_glm_row (table, 0, ssq, df, ssq / df, F,
+ gsl_cdf_fdist_Q (F, df, n_total - df_corr));
}
{
+ int row = pivot_category_create_leaf (source->root,
+ pivot_value_new_text (N_("Error")));
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);
+ put_glm_row (table, row, ssq, df, mse, SYSMIS, SYSMIS);
}
{
- tab_text (t, 0, r, TAB_LEFT | TAT_TITLE, _("Total"));
- tab_double (t, 1, r, 0, ws->total_ssq + intercept_ssq, NULL);
- tab_double (t, 2, r, 0, n_total, wfmt);
-
- r++;
+ int row = pivot_category_create_leaf (source->root,
+ pivot_value_new_text (N_("Total")));
+ put_glm_row (table, row, ws->total_ssq + intercept_ssq, n_total,
+ SYSMIS, SYSMIS, SYSMIS);
}
if (cmd->intercept)
{
- 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);
+ int row = pivot_category_create_leaf (
+ source->root, pivot_value_new_text (N_("Corrected Total")));
+ put_glm_row (table, row, ws->total_ssq, n_total - 1.0, SYSMIS,
+ SYSMIS, SYSMIS);
}
- tab_submit (t);
+ pivot_table_submit (table);
}
#if 0
\f
-
-/* Match a variable.
- If the match succeeds, the variable will be placed in VAR.
- Returns true if successful */
-static bool
-lex_match_variable (struct lexer *lexer, const struct dictionary *dict, const struct variable **var)
-{
- if (lex_token (lexer) != T_ID)
- return false;
-
- *var = parse_variable_const (lexer, dict);
-
- if ( *var == NULL)
- return false;
- return true;
-}
-
-/* An interaction is a variable followed by {*, BY} followed by an interaction */
-static bool
-parse_design_interaction (struct lexer *lexer, const struct dictionary *dict, struct interaction **iact)
-{
- const struct variable *v = NULL;
- assert (iact);
-
- switch (lex_next_token (lexer, 1))
- {
- case T_ENDCMD:
- case T_SLASH:
- case T_COMMA:
- case T_ID:
- case T_BY:
- case T_ASTERISK:
- break;
- default:
- return false;
- break;
- }
-
- if (! lex_match_variable (lexer, dict, &v))
- {
- interaction_destroy (*iact);
- *iact = NULL;
- return false;
- }
-
- assert (v);
-
- if ( *iact == NULL)
- *iact = interaction_create (v);
- else
- interaction_add_variable (*iact, v);
-
- if ( lex_match (lexer, T_ASTERISK) || lex_match (lexer, T_BY))
- {
- return parse_design_interaction (lexer, dict, iact);
- }
-
- return true;
-}
-
static bool
parse_nested_variable (struct lexer *lexer, struct glm_spec *glm)
{
const struct variable *v = NULL;
- if ( ! lex_match_variable (lexer, glm->dict, &v))
+ if (! lex_match_variable (lexer, glm->dict, &v))
return false;
if (lex_match (lexer, T_LPAREN))
{
- if ( ! parse_nested_variable (lexer, glm))
+ if (! parse_nested_variable (lexer, glm))
return false;
- if ( ! lex_force_match (lexer, T_RPAREN))
+ if (! lex_force_match (lexer, T_RPAREN))
return false;
}
- lex_error (lexer, "Nested variables are not yet implemented"); return false;
+ lex_error (lexer, "Nested variables are not yet implemented"); return false;
return true;
}
return true;
}
- if ( parse_nested_variable (lexer, glm))
+ if (parse_nested_variable (lexer, glm))
return true;
return false;
if (lex_token (lexer) == T_ENDCMD || lex_token (lexer) == T_SLASH)
return true;
- if ( ! parse_design_term (lexer, glm))
+ if (! parse_design_term (lexer, glm))
return false;
lex_match (lexer, T_COMMA);
projects / pspp / blobdiff