+ 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);