/* PSPP - a program for statistical analysis.
- Copyright (C) 2005, 2010, 2011 Free Software Foundation, Inc.
+ Copyright (C) 2005, 2010, 2011, 2017 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
*/
linreg *
linreg_alloc (const struct variable *depvar, const struct variable **indep_vars,
- double n, size_t p)
+ double n, size_t p, bool origin)
{
linreg *c;
size_t i;
c->indep_means = gsl_vector_alloc (p);
c->indep_std = gsl_vector_alloc (p);
- c->ss_indeps = gsl_vector_alloc (p); /* Sums of squares for the
- model parameters.
- */
c->n_obs = n;
c->n_indeps = p;
c->n_coeffs = p;
c->coeff = xnmalloc (p, sizeof (*c->coeff));
c->cov = gsl_matrix_calloc (c->n_coeffs + 1, c->n_coeffs + 1);
- c->dft = n - 1;
+ c->dft = n;
+ if (!origin)
+ c->dft--;
+
c->dfm = p;
c->dfe = c->dft - c->dfm;
c->intercept = 0.0;
c->depvar_mean = 0.0;
- c->depvar_std = 0.0;
/*
Default settings.
*/
c->method = LINREG_SWEEP;
- c->pred = NULL;
- c->resid = NULL;
c->refcnt = 1;
+
+ c->origin = origin;
+
return c;
}
+
void
linreg_ref (linreg *c)
{
void
linreg_unref (linreg *c)
{
- if (c && --c->refcnt == 0)
+ if (--c->refcnt == 0)
{
gsl_vector_free (c->indep_means);
gsl_vector_free (c->indep_std);
- gsl_vector_free (c->ss_indeps);
gsl_matrix_free (c->cov);
free (c->indep_vars);
free (c->coeff);
static void
post_sweep_computations (linreg *l, gsl_matrix *sw)
{
- gsl_matrix *xm;
- gsl_matrix_view xtx;
- gsl_matrix_view xmxtx;
double m;
- double tmp;
size_t i;
size_t j;
int rc;
-
+
assert (sw != NULL);
assert (l != NULL);
m = l->depvar_mean;
for (i = 0; i < l->n_indeps; i++)
{
- tmp = gsl_matrix_get (sw, i, l->n_indeps);
+ double tmp = gsl_matrix_get (sw, i, l->n_indeps);
l->coeff[i] = tmp;
m -= tmp * linreg_get_indep_variable_mean (l, i);
}
Get the covariance matrix of the parameter estimates.
Only the upper triangle is necessary.
*/
-
+
/*
The loops below do not compute the entries related
to the estimated intercept.
for (i = 0; i < l->n_indeps; i++)
for (j = i; j < l->n_indeps; j++)
{
- tmp = -1.0 * l->mse * gsl_matrix_get (sw, i, j);
+ double tmp = -1.0 * l->mse * gsl_matrix_get (sw, i, j);
gsl_matrix_set (l->cov, i + 1, j + 1, tmp);
}
- /*
- Get the covariances related to the intercept.
- */
- xtx = gsl_matrix_submatrix (sw, 0, 0, l->n_indeps, l->n_indeps);
- xmxtx = gsl_matrix_submatrix (l->cov, 0, 1, 1, l->n_indeps);
- xm = gsl_matrix_calloc (1, l->n_indeps);
- for (i = 0; i < xm->size2; i++)
- {
- gsl_matrix_set (xm, 0, i,
- linreg_get_indep_variable_mean (l, i));
- }
- rc = gsl_blas_dsymm (CblasRight, CblasUpper, l->mse,
- &xtx.matrix, xm, 0.0, &xmxtx.matrix);
- gsl_matrix_free (xm);
- if (rc == GSL_SUCCESS)
+
+ if (! l->origin)
{
- tmp = l->mse / l->n_obs;
- for (i = 1; i < 1 + l->n_indeps; i++)
+ gsl_matrix *xm;
+ gsl_matrix_view xtx;
+ gsl_matrix_view xmxtx;
+ /*
+ Get the covariances related to the intercept.
+ */
+ xtx = gsl_matrix_submatrix (sw, 0, 0, l->n_indeps, l->n_indeps);
+ xmxtx = gsl_matrix_submatrix (l->cov, 0, 1, 1, l->n_indeps);
+ xm = gsl_matrix_calloc (1, l->n_indeps);
+ for (i = 0; i < xm->size2; i++)
{
- tmp -= gsl_matrix_get (l->cov, 0, i)
- * linreg_get_indep_variable_mean (l, i - 1);
+ gsl_matrix_set (xm, 0, i,
+ linreg_get_indep_variable_mean (l, i));
+ }
+ rc = gsl_blas_dsymm (CblasRight, CblasUpper, l->mse,
+ &xtx.matrix, xm, 0.0, &xmxtx.matrix);
+ gsl_matrix_free (xm);
+ if (rc == GSL_SUCCESS)
+ {
+ double tmp = l->mse / l->n_obs;
+ for (i = 1; i < 1 + l->n_indeps; i++)
+ {
+ tmp -= gsl_matrix_get (l->cov, 0, i)
+ * linreg_get_indep_variable_mean (l, i - 1);
+ }
+ gsl_matrix_set (l->cov, 0, 0, tmp);
+
+ l->intercept = m;
+ }
+ else
+ {
+ fprintf (stderr, "%s:%d:gsl_blas_dsymm: %s\n",
+ __FILE__, __LINE__, gsl_strerror (rc));
+ exit (rc);
}
- gsl_matrix_set (l->cov, 0, 0, tmp);
-
- l->intercept = m;
- }
- else
- {
- fprintf (stderr, "%s:%d:gsl_blas_dsymm: %s\n",
- __FILE__, __LINE__, gsl_strerror (rc));
- exit (rc);
}
-}
+}
/*
Predict the value of the dependent variable with the new set of
return (obs - linreg_predict (c, vals, n_vals));
}
-double linreg_get_indep_variable_sd (linreg *c, size_t j)
-{
- assert (c != NULL);
- return gsl_vector_get (c->indep_std, j);
-}
-
-void linreg_set_indep_variable_sd (linreg *c, size_t j, double s)
-{
- assert (c != NULL);
- gsl_vector_set (c->indep_std, j, s);
-}
-
/*
Mean of the independent variable.
*/
-double linreg_get_indep_variable_mean (linreg *c, size_t j)
+double linreg_get_indep_variable_mean (const linreg *c, size_t j)
{
assert (c != NULL);
return gsl_vector_get (c->indep_means, j);
gsl_vector *xty;
gsl_vector *tau;
gsl_vector *params;
- double tmp = 0.0;
size_t i;
size_t j;
}
}
l->intercept = linreg_get_depvar_mean (l);
- tmp = 0.0;
for (i = 0; i < l->n_indeps; i++)
{
- tmp = linreg_get_indep_variable_mean (l, i);
+ double tmp = linreg_get_indep_variable_mean (l, i);
l->intercept -= l->coeff[i] * tmp;
intercept_variance += tmp * tmp * gsl_matrix_get (q, i, i);
}
/* Covariances related to the intercept. */
intercept_variance += linreg_mse (l) / linreg_n_obs (l);
- gsl_matrix_set (l->cov, 0, 0, intercept_variance);
+ gsl_matrix_set (l->cov, 0, 0, intercept_variance);
for (i = 0; i < q->size1; i++)
{
for (j = 0; j < q->size2; j++)
{
- intcpt_coef -= gsl_matrix_get (q, i, j)
+ intcpt_coef -= gsl_matrix_get (q, i, j)
* linreg_get_indep_variable_mean (l, j);
}
gsl_matrix_set (l->cov, 0, i + 1, intcpt_coef);
gsl_matrix_set (l->cov, i + 1, 0, intcpt_coef);
intcpt_coef = 0.0;
}
-
+
gsl_matrix_free (q);
gsl_matrix_free (r);
gsl_vector_free (xty);
params = gsl_matrix_calloc (cov->size1, cov->size2);
gsl_matrix_memcpy (params, cov);
reg_sweep (params, l->dependent_column);
- post_sweep_computations (l, params);
+ post_sweep_computations (l, params);
gsl_matrix_free (params);
}
else if (l->method == LINREG_QR)
return c->intercept;
}
-gsl_matrix *
+const gsl_matrix *
linreg_cov (const linreg *c)
{
return c->cov;
}
-double
+double
linreg_coeff (const linreg *c, size_t i)
{
return (c->coeff[i]);
return (c->indep_vars[i]);
}
-size_t
+size_t
linreg_n_coeffs (const linreg *c)
{
return c->n_coeffs;
return c->sst;
}
-double
+double
linreg_dfmodel ( const linreg *c)
{
return c->dfm;
c->depvar_mean = x;
}
-double
-linreg_get_depvar_mean (linreg *c)
+double
+linreg_get_depvar_mean (const linreg *c)
{
return c->depvar_mean;
}
projects / pspp / blobdiff