if (!gsl_isnan (x))
{
x -= est[j]->mean;
- for (lag = 1; lag <= max_lag && lag < data->size1 - max_lag; lag++)
+ for (lag = 1; lag <= max_lag && lag < (data->size1 - i); lag++)
{
y = gsl_matrix_get (data, i + lag, j);
if (!gsl_isnan (y))
{
y -= est[j]->mean;
- *(est[j]->cov + lag) += y * x;
+ *(est[j]->cov + lag - 1) += y * x;
est[j]->n_obs += 1.0;
}
}
}
}
}
- for (lag = 0; lag <= max_lag && lag < data->size1 - max_lag; lag++)
+ for (lag = 1; lag <= max_lag; lag++)
{
for (j = 0; j < data->size2; j++)
{
- *(est[j]->cov + lag) /= (est[j]->n_obs - lag);
+ *(est[j]->cov + lag - 1) /= (est[j]->n_obs - lag);
}
}
return rc;
size_t j;
size_t k;
-
- result = est->cov[0];
- for (j = 0; j < i; j++)
+ if (i < (size_t) est->max_lag)
{
- k = i - j;
- result -= theta[k] * theta[k] * est->scale[j];
+ result = est->variance;
+ for (j = 0; j < i; j++)
+ {
+ k = i - j - 1;
+ result -= theta[k] * theta[k] * est->scale[j];
+ }
+ est->scale[i] = result;
}
- est->scale[i] = result;
}
static void
init_theta (double **theta, size_t max_lag)
size_t i;
size_t j;
size_t k;
- double v;
for (i = 0; i < max_lag; i++)
{
- v = est->cov[i];
- for (j = 0; j < i; j++)
+ for (j = 0; j <= i; j++)
{
k = i - j;
- theta[i-1][k-1] = est->cov[k] -
- innovations_convolve (theta, est, i, j);
+ theta[i][k] = (est->cov[k] -
+ innovations_convolve (theta, est, i, j))
+ / est->scale[k];
}
- innovations_update_scale (est, theta[i], i);
+ innovations_update_scale (est, theta[i], i + 1);
}
}
static void
theta = xnmalloc (max_lag, sizeof (*theta));
for (i = 0; i < max_lag; i++)
{
- theta[i] = xnmalloc (i + 1, sizeof (**(theta + i)));
+ theta[i] = xnmalloc (max_lag, sizeof (**(theta + i)));
}
for (n = 0; n < data->size2; n++)
free (theta);
}
+static void
+innovations_struct_init (struct innovations_estimate *est, size_t lag)
+{
+ size_t j;
+
+ est->mean = 0.0;
+ est->variance = 0.0;
+ est->cov = xnmalloc (lag, sizeof (*est->cov));
+ est->scale = xnmalloc (lag + 1, sizeof (*est->scale));
+ est->coeff = xnmalloc (lag, sizeof (*est->coeff));
+ est->max_lag = (double) lag;
+ /* COV does not the variance (i.e., the lag 0 covariance). So COV[0]
+ holds the lag 1 covariance, COV[i] holds the lag i+1 covariance. */
+ for (j = 0; j < lag; j++)
+ {
+ est->coeff[j] = xmalloc (sizeof (*(est->coeff[j])));
+ }
+}
+
struct innovations_estimate **
pspp_innovations (const gsl_matrix *data, size_t lag)
{
struct innovations_estimate **est;
size_t i;
- size_t j;
est = xnmalloc (data->size2, sizeof *est);
for (i = 0; i < data->size2; i++)
{
- est[i] = xmalloc (sizeof **est);
+ est[i] = xmalloc (sizeof *est[i]);
/* est[i]->variable = vars[i]; */
- est[i]->mean = 0.0;
- est[i]->variance = 0.0;
- est[i]->cov = xnmalloc (lag, sizeof (*est[i]->cov));
- est[i]->scale = xnmalloc (lag, sizeof (*est[i]->scale));
- est[i]->coeff = xnmalloc (lag, sizeof (*est[i]->coeff));
- for (j = 0; j < lag; j++)
- {
- est[i]->coeff[j] = xmalloc (sizeof (*(est[i]->coeff + j)));
- }
+ innovations_struct_init (est[i], lag);
}
get_mean_variance (data, est);
return est;
}
+
+static void
+pspp_innovations_free_one (struct innovations_estimate *est)
+{
+ size_t i;
+
+ assert (est != NULL);
+ for (i = 0; i < (size_t) est->max_lag; i++)
+ {
+ pspp_coeff_free (est->coeff[i]);
+ }
+ free (est->scale);
+ free (est->cov);
+ free (est);
+}
+
+void pspp_innovations_free (struct innovations_estimate **est, size_t n)
+{
+ size_t i;
+
+ assert (est != NULL);
+ for (i = 0; i < n; i++)
+ {
+ pspp_innovations_free_one (est[i]);
+ }
+ free (est);
+}