0-387-97429-6. Sections 5.2, 8.3 and 8.4.
*/
+#include <config.h>
#include <gsl/gsl_matrix.h>
#include <gsl/gsl_vector.h>
#include <gsl/gsl_math.h>
*/
for (i = 0; i < data->size1; i++)
{
- for (lag = 0; lag < max_lag && lag < data->size1 - i; lag++)
+ for (lag = 0; lag <= max_lag && lag < data->size1 - i; lag++)
{
update_cov (est, gsl_matrix_const_row (data, i),
gsl_matrix_const_row (data, i + lag), lag);
}
static double
-innovations_convolve (double **theta, struct innovations_estimate *est,
- int i, int j)
+innovations_convolve (double *x, double *y, struct innovations_estimate *est,
+ int i)
{
int k;
double result = 0.0;
- for (k = 0; k < j; k++)
+ assert (x != NULL && y != NULL);
+ assert (est != NULL);
+ assert (est->scale != NULL);
+ assert (i > 0);
+ for (k = 0; k < i; k++)
{
- result += theta[i-1][i-k-1] * theta[j][j-k-1] * est->scale[k];
+ result += x[k] * y[k] * est->scale[i-k-1];
}
return result;
}
for (i = 0; i < max_lag; i++)
{
- for (j = 0; j <= i; j++)
+ theta[i][i] = est->cov[i+1] / est->scale[0];
+ for (j = 1; j <= i; j++)
{
k = i - j;
- theta[i][k] = (est->cov[k] -
- innovations_convolve (theta, est, i, j))
- / est->scale[k];
+ theta[i][k] = (est->cov[k+1] -
+ innovations_convolve (theta[i] + k + 1, theta[j - 1], est, j))
+ / est->scale[j];
}
innovations_update_scale (est, theta[i], i + 1);
}
+ est->coeff[m-1] * (X[m-2] - X_hat[m-2])
...
+ est->coeff[m-max_lag] * (X[m - max_lag] - X_hat[m - max_lag])
-
- (That is what X_hat[m] SHOULD be, anyway. These routines need
- to be tested.)
*/
pspp_coeff_set_estimate (est[n]->coeff[i], theta[max_lag - 1][i]);
}
}
est->max_lag = (double) lag;
}
-
+/*
+ The mean is subtracted from the original data before computing the
+ coefficients. The mean is NOT added back, so if you want to predict
+ a new value, you must add the mean to X_hat[m] to get the correct
+ value.
+ */
+static void
+subtract_mean (gsl_matrix *m, struct innovations_estimate **est)
+{
+ size_t i;
+ size_t j;
+ double tmp;
+
+ for (i = 0; i < m->size1; i++)
+ {
+ for (j = 0; j < m->size2; j++)
+ {
+ tmp = gsl_matrix_get (m, i, j) - est[j]->mean;
+ gsl_matrix_set (m, i, j, tmp);
+ }
+ }
+}
struct innovations_estimate **
pspp_innovations (const struct design_matrix *dm, size_t lag)
{
}
get_mean (dm->m, est);
+ subtract_mean (dm->m, est);
get_covariance (dm->m, est, lag);
get_coef (dm->m, est, lag);