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[i]->n_obs += 1.0;
+ *(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++)
{
int k;
double result = 0.0;
- for (k = 0; k < i; k++)
+ for (k = 0; k < j; k++)
{
- result += theta[i-1][i-k-1] * theta[j-1][j-k-1] * est->scale[k];
+ result += theta[i-1][i-k-1] * theta[j][j-k-1] * est->scale[k];
}
return result;
}
size_t k;
- result = est->cov[0];
+ result = est->variance;
for (j = 0; j < i; j++)
{
- k = i - j;
+ k = i - j - 1;
result -= theta[k] * theta[k] * est->scale[j];
}
est->scale[i] = result;
}
+static void
+init_theta (double **theta, size_t max_lag)
+{
+ size_t i;
+ size_t j;
+ for (i = 0; i < max_lag; i++)
+ {
+ for (j = 0; j <= i; j++)
+ {
+ theta[i][j] = 0.0;
+ }
+ }
+}
+static void
+innovations_update_coeff (double **theta, struct innovations_estimate *est,
+ size_t max_lag)
+{
+ size_t i;
+ size_t j;
+ size_t k;
+ double v;
+
+ for (i = 0; i < max_lag; i++)
+ {
+ for (j = 0; j <= i; j++)
+ {
+ k = i - j;
+ theta[i][k] = (est->cov[k] -
+ innovations_convolve (theta, est, i, j))
+ / est->scale[k];
+ }
+ innovations_update_scale (est, theta[i], i + 1);
+ }
+}
static void
get_coef (const gsl_matrix *data,
struct innovations_estimate **est, size_t max_lag)
{
- size_t j;
size_t i;
- size_t k;
size_t n;
- double v;
double **theta;
theta = xnmalloc (max_lag, sizeof (*theta));
for (i = 0; i < max_lag; i++)
{
- theta[i] = xnmalloc (i+1, sizeof (theta[i]));
-
+ theta[i] = xnmalloc (i + 1, sizeof (**(theta + i)));
}
+
for (n = 0; n < data->size2; n++)
{
- for (i = 0; i < max_lag; i++)
- {
- for (j = 0; j < i; j++)
- {
- theta[i][j] = 0.0;
- }
- }
+ init_theta (theta, max_lag);
innovations_update_scale (est[n], theta[0], 0);
- for (i = 0; i < max_lag; i++)
- {
- v = est[n]->cov[i];
- for (j = 0; j < i; j++)
- {
- k = i - j;
- theta[i-1][k-1] = est[n]->cov[k] -
- innovations_convolve (theta, est[n], i, j);
- }
- innovations_update_scale (est[n], theta[i], i);
- }
+ innovations_update_coeff (theta, est[n], max_lag);
/* Copy the final row of coefficients into EST->COEFF.*/
for (i = 0; i < max_lag; i++)
{
pspp_coeff_set_estimate (est[n]->coeff[i], theta[max_lag - 1][i]);
}
}
+
for (i = 0; i < max_lag; i++)
{
free (theta[i]);
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;
+ /* 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. */
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));
+ est[i]->max_lag = (double) lag;
for (j = 0; j < lag; j++)
{
est[i]->coeff[j] = xmalloc (sizeof (*(est[i]->coeff + j)));
return est;
}
+
+static void
+pspp_innovations_free_one (struct innovations_estimate *est)
+{
+ size_t i;
+
+ assert (est != NULL);
+ free (est->cov);
+ free (est->scale);
+ for (i = 0; i < (size_t) est->max_lag; i++)
+ {
+ pspp_coeff_free (est->coeff[i]);
+ }
+}
+
+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);
+}