all;
export=custom;
^dependent=varlist;
- ^method=enter.
+ method=enter.
*/
/* (declarations) */
/* (functions) */
statistics_keyword_output (reg_stats_tol, keywords[tol], c);
statistics_keyword_output (reg_stats_selection, keywords[selection], c);
}
-static
-int reg_inserted (struct variable *v, struct variable **varlist, int n_vars)
+static int
+reg_inserted (struct variable *v, struct variable **varlist, int n_vars)
{
int i;
return 0;
}
static void
-reg_print_categorical_encoding (FILE *fp, pspp_linreg_cache *c)
+reg_print_categorical_encoding (FILE * fp, pspp_linreg_cache * c)
{
int i;
size_t j;
struct variable **varlist;
struct pspp_linreg_coeff coeff;
union value *val;
-
+
fprintf (fp, "%s", reg_export_categorical_encode_1);
varlist = xnmalloc (c->n_indeps, sizeof (*varlist));
- for (i = 1; i < c->n_indeps; i++) /* c->coeff[0] is the intercept. */
+ for (i = 1; i < c->n_indeps; i++) /* c->coeff[0] is the intercept. */
{
coeff = c->coeff[i];
if (coeff.v->type == ALPHA)
{
if (!reg_inserted (coeff.v, varlist, n_vars))
- {
- fprintf (fp, "struct pspp_reg_categorical_variable %s;\n\t", coeff.v->name);
- varlist[n_vars] = coeff.v;
- n_vars++;
- }
+ {
+ fprintf (fp, "struct pspp_reg_categorical_variable %s;\n\t",
+ coeff.v->name);
+ varlist[n_vars] = coeff.v;
+ n_vars++;
+ }
}
}
fprintf (fp, "int n_vars = %d;\n\t", n_vars);
- fprintf (fp, "struct pspp_reg_categorical_variable *varlist[%d] = {", n_vars);
+ fprintf (fp, "struct pspp_reg_categorical_variable *varlist[%d] = {",
+ n_vars);
for (i = 0; i < n_vars - 1; i++)
{
fprintf (fp, "&%s,\n\t\t", varlist[i]->name);
for (i = 0; i < n_vars; i++)
{
coeff = c->coeff[i];
- fprintf (fp, "%s.name = \"%s\";\n\t", varlist[i]->name, varlist[i]->name);
- fprintf (fp, "%s.n_vals = %d;\n\t", varlist[i]->name, varlist[i]->obs_vals->n_categories);
+ fprintf (fp, "%s.name = \"%s\";\n\t", varlist[i]->name,
+ varlist[i]->name);
+ fprintf (fp, "%s.n_vals = %d;\n\t", varlist[i]->name,
+ varlist[i]->obs_vals->n_categories);
for (j = 0; j < varlist[i]->obs_vals->n_categories; j++)
{
- val = cat_subscript_to_value ( (const size_t) j, varlist[i]);
- fprintf (fp, "%s.values[%d] = \"%s\";\n\t", varlist[i]->name, j, value_to_string (val, varlist[i]));
+ val = cat_subscript_to_value ((const size_t) j, varlist[i]);
+ fprintf (fp, "%s.values[%d] = \"%s\";\n\t", varlist[i]->name, j,
+ value_to_string (val, varlist[i]));
}
}
fprintf (fp, "%s", reg_export_categorical_encode_2);
}
static void
-reg_print_depvars (FILE *fp, pspp_linreg_cache *c)
+reg_print_depvars (FILE * fp, pspp_linreg_cache * c)
{
int i;
struct pspp_linreg_coeff coeff;
fprintf (fp, "\"%s\"};\n\t", coeff.v->name);
}
static void
-reg_print_getvar (FILE *fp, pspp_linreg_cache *c)
+reg_print_getvar (FILE * fp, pspp_linreg_cache * c)
{
fprintf (fp, "static int\npspp_reg_getvar (char *v_name)\n{\n\t");
- fprintf (fp, "int i;\n\tint n_vars = %d;\n\t",c->n_indeps);
+ fprintf (fp, "int i;\n\tint n_vars = %d;\n\t", c->n_indeps);
reg_print_depvars (fp, c);
fprintf (fp, "for (i = 0; i < n_vars; i++)\n\t{\n\t\t");
- fprintf (fp, "if (strncmp (v_name, model_depvars[i], PSPP_REG_MAXLEN) == 0)\n\t\t{\n\t\t\t");
+ fprintf (fp,
+ "if (strncmp (v_name, model_depvars[i], PSPP_REG_MAXLEN) == 0)\n\t\t{\n\t\t\t");
fprintf (fp, "return i;\n\t\t}\n\t}\n}\n");
}
static void
-subcommand_export (int export, pspp_linreg_cache *c)
+subcommand_export (int export, pspp_linreg_cache * c)
{
FILE *fp;
size_t i;
for (i = 0; i < n_quantiles - 1; i++)
{
tmp = 0.5 + 0.005 * (double) i;
- fprintf (fp, "%.15e,\n\t\t", gsl_cdf_tdist_Pinv (tmp, c->n_obs - c->n_indeps));
+ fprintf (fp, "%.15e,\n\t\t",
+ gsl_cdf_tdist_Pinv (tmp, c->n_obs - c->n_indeps));
}
- fprintf (fp, "%.15e};\n\t", gsl_cdf_tdist_Pinv (.9995, c->n_obs - c->n_indeps));
+ fprintf (fp, "%.15e};\n\t",
+ gsl_cdf_tdist_Pinv (.9995, c->n_obs - c->n_indeps));
fprintf (fp, "%s", reg_export_t_quantiles_2);
fprintf (fp, "%s", reg_mean_cmt);
fprintf (fp, "double\npspp_reg_estimate (const double *var_vals,");
fprintf (fp, "int i;\n\tint j;\n\n\t");
fprintf (fp, "for (i = 0; i < %d; i++)\n\t", c->n_indeps);
fprintf (fp, "%s", reg_getvar);
- fprintf (fp, "const double cov[%d][%d] = {\n\t", c->n_coeffs, c->n_coeffs);
+ fprintf (fp, "const double cov[%d][%d] = {\n\t", c->n_coeffs,
+ c->n_coeffs);
for (i = 0; i < c->cov->size1 - 1; i++)
{
fprintf (fp, "{");
fprintf (fp, "{");
for (j = 0; j < c->cov->size2 - 1; j++)
{
- fprintf (fp, "%.15e, ", gsl_matrix_get (c->cov, c->cov->size1 - 1, j));
+ fprintf (fp, "%.15e, ",
+ gsl_matrix_get (c->cov, c->cov->size1 - 1, j));
}
- fprintf (fp, "%.15e}\n\t", gsl_matrix_get (c->cov, c->cov->size1 - 1, c->cov->size2 - 1));
- fprintf (fp, "};\n\tint n_vars = %d;\n\tint i;\n\tint j;\n\t", c->n_indeps);
- fprintf (fp, "double unshuffled_vals[%d];\n\t",c->n_indeps);
+ fprintf (fp, "%.15e}\n\t",
+ gsl_matrix_get (c->cov, c->cov->size1 - 1, c->cov->size2 - 1));
+ fprintf (fp, "};\n\tint n_vars = %d;\n\tint i;\n\tint j;\n\t",
+ c->n_indeps);
+ fprintf (fp, "double unshuffled_vals[%d];\n\t", c->n_indeps);
fprintf (fp, "%s", reg_variance);
fprintf (fp, "%s", reg_export_confidence_interval);
tmp = c->mse * c->mse;
/* 0 on failure, 1 on success, 2 on failure that should result in syntax error */
if (!lex_force_match ('('))
return 0;
-
+
if (lex_match ('*'))
model_file = NULL;
- else
+ else
{
model_file = fh_parse ();
if (model_file == NULL)
- return 0;
+ return 0;
}
-
+
if (!lex_force_match (')'))
return 0;
return 0;
}
+/*
+ Mark missing cases. Return the number of non-missing cases.
+ */
+static size_t
+mark_missing_cases (const struct casefile *cf, struct variable *v,
+ double *is_missing_case, double n_data)
+{
+ struct casereader *r;
+ struct ccase c;
+ size_t row;
+ union value *val;
+
+ for (r = casefile_get_reader (cf);
+ casereader_read (r, &c); case_destroy (&c))
+ {
+ row = casereader_cnum (r) - 1;
+
+ val = case_data (&c, v->fv);
+ 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;
+ }
+ }
+ }
+ casereader_destroy (r);
+
+ return n_data;
+}
static void
run_regression (const struct casefile *cf, void *cmd_ UNUSED)
{
size_t case_num;
int n_indep;
int j = 0;
+ int k;
/*
Keep track of the missing cases.
*/
int *is_missing_case;
const union value *val;
struct casereader *r;
- struct casereader *r2;
struct ccase c;
struct variable *v;
+ struct variable *depvar;
struct variable **indep_vars;
struct design_matrix *X;
gsl_vector *Y;
n_data = casefile_get_case_cnt (cf);
+ for (i = 0; i < cmd.n_dependent; i++)
+ {
+ if (cmd.v_dependent[i]->type != NUMERIC)
+ {
+ msg (SE, gettext ("Dependent variable must be numeric."));
+ pspp_reg_rc = CMD_FAILURE;
+ return;
+ }
+ }
+
is_missing_case = xnmalloc (n_data, sizeof (*is_missing_case));
for (i = 0; i < n_data; i++)
is_missing_case[i] = 0;
lopts.get_depvar_mean_std = 1;
lopts.get_indep_mean_std = xnmalloc (n_indep, sizeof (int));
-
/*
Read from the active file. The first pass encodes categorical
variables and drops cases with missing values.
if (v->type == ALPHA)
{
/* Make a place to hold the binary vectors
- corresponding to this variable's values. */
+ 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);
- 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;
- }
- }
- }
+ n_data = mark_missing_cases (cf, v, is_missing_case, n_data);
}
}
- Y = gsl_vector_alloc (n_data);
- X =
- design_matrix_create (n_indep, (const struct variable **) indep_vars,
- 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.
+ Drop cases with missing values for any dependent variable.
*/
- row = 0;
- for (r2 = casefile_get_reader (cf); casereader_read (r2, &c);
- case_destroy (&c))
- /* Iterate over the cases. */
+ j = 0;
+ for (i = 0; i < cmd.n_dependent; i++)
+ {
+ v = cmd.v_dependent[i];
+ j++;
+ n_data = mark_missing_cases (cf, v, is_missing_case, n_data);
+ }
+
+ for (k = 0; k < cmd.n_dependent; k++)
{
- case_num = casereader_cnum (r2) - 1;
- if (!is_missing_case[case_num])
+ depvar = cmd.v_dependent[k];
+ Y = gsl_vector_alloc (n_data);
+
+ X =
+ design_matrix_create (n_indep, (const struct variable **) indep_vars,
+ 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);
+ lcache->depvar = (const struct variable *) depvar;
+ /*
+ For large data sets, use QR decomposition.
+ */
+ if (n_data > sqrt (n_indep) && n_data > REG_LARGE_DATA)
{
- for (i = 0; i < cmd.n_variables; ++i) /* Iterate over the variables
- for the current case.
- */
+ lcache->method = PSPP_LINREG_SVD;
+ }
+
+ /*
+ The second pass creates the design matrix.
+ */
+ row = 0;
+ for (r = casefile_get_reader (cf); casereader_read (r, &c);
+ case_destroy (&c))
+ /* Iterate over the cases. */
+ {
+ case_num = casereader_cnum (r) - 1;
+ if (!is_missing_case[case_num])
{
- 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))
+ for (i = 0; i < cmd.n_variables; ++i) /* Iterate over the variables
+ for the current case.
+ */
{
- 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, and maybe also in the 'variables' 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 == ALPHA)
+ {
+ design_matrix_set_categorical (X, row, v, val);
+ }
+ else if (v->type == NUMERIC)
+ {
+ design_matrix_set_numeric (X, row, v, val);
+ }
+ lopts.get_indep_mean_std[i] = 1;
}
- lcache->depvar = (const struct variable *) v;
- gsl_vector_set (Y, row, val->f);
- }
- else
- {
- 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);
- }
-
- lopts.get_indep_mean_std[i] = 1;
}
+ val = case_data (&c, depvar->fv);
+ gsl_vector_set (Y, row, val->f);
+ row++;
}
- row++;
}
+ /*
+ Now that we know the number of coefficients, allocate space
+ and store pointers to the variables that correspond to the
+ coefficients.
+ */
+ lcache->coeff = xnmalloc (X->m->size2 + 1, sizeof (*lcache->coeff));
+ for (i = 0; i < X->m->size2; i++)
+ {
+ 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.
+ */
+ pspp_linreg ((const gsl_vector *) Y, X->m, &lopts, lcache);
+ subcommand_statistics (cmd.a_statistics, lcache);
+ subcommand_export (cmd.sbc_export, lcache);
+ gsl_vector_free (Y);
+ design_matrix_destroy (X);
+ pspp_linreg_cache_free (lcache);
+ free (lopts.get_indep_mean_std);
+ casereader_destroy (r);
}
- /*
- Now that we know the number of coefficients, allocate space
- and store pointers to the variables that correspond to the
- coefficients.
- */
- lcache->coeff = xnmalloc (X->m->size2 + 1, sizeof (*lcache->coeff));
- for (i = 0; i < X->m->size2; i++)
- {
- 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);
- }
- /*
- For large data sets, use QR decomposition.
- */
- if (n_data > sqrt (n_indep) && n_data > REG_LARGE_DATA)
- {
- lcache->method = PSPP_LINREG_SVD;
- }
- /*
- Find the least-squares estimates and other statistics.
- */
- pspp_linreg ((const gsl_vector *) Y, X->m, &lopts, lcache);
- subcommand_statistics (cmd.a_statistics, lcache);
- subcommand_export (cmd.sbc_export, lcache);
- gsl_vector_free (Y);
- design_matrix_destroy (X);
- pspp_linreg_cache_free (lcache);
- free (lopts.get_indep_mean_std);
free (indep_vars);
free (is_missing_case);
- casereader_destroy (r);
+
return;
}
projects / pspp-builds.git / commitdiff