/*
- src/math/time-series/arma/innovations.c
+ src/math/ts/innovations.c
Copyright (C) 2006 Free Software Foundation, Inc. Written by Jason H. Stover.
Read the first MAX_LAG cases.
*/
static bool
-innovations_init_cases (struct casereader *r, struct ccase **c, size_t max_lag)
+innovations_init_cases (struct casereader *r, struct ccase **inn_cs, size_t max_lag)
{
bool value = true;
size_t lag = 0;
+ assert (r != NULL);
+ assert (inn_cs != NULL);
while (value && lag < max_lag)
{
+ assert (inn_cs[lag] != NULL);
+ value = casereader_read (r, inn_cs[lag]);
lag++;
- value = casereader_read (r, c[lag]);
}
return value;
}
struct innovations_estimate **est, size_t max_lag)
{
struct casereader *r;
- struct ccase **c;
+ struct ccase **inn_c;
size_t lag;
size_t n;
bool read_case = false;
const union value *tmp;
const union value *tmp2;
- c = xnmalloc (max_lag, sizeof (*c));
+ inn_c = xnmalloc (max_lag, sizeof (*inn_c));
for (lag = 0; lag < max_lag; lag++)
{
- c[lag] = xmalloc (sizeof *c[lag]);
+ inn_c[lag] = xmalloc (sizeof *inn_c[lag]);
}
r = casefile_get_reader (cf);
- read_case = innovations_init_cases (r, c, max_lag);
+ read_case = innovations_init_cases (r, inn_c, max_lag);
while (read_case)
{
for (n = 0; n < n_vars; n++)
{
- tmp2 = case_data (c[0], est[n]->variable->fv);
+ tmp2 = case_data (inn_c[0], est[n]->variable->fv);
if (!mv_is_value_missing (&est[n]->variable->miss, tmp2))
{
x = tmp2->f - est[n]->mean;
for (lag = 1; lag <= max_lag; lag++)
{
- tmp = case_data (c[lag], est[n]->variable->fv);
+ tmp = case_data (inn_c[lag], est[n]->variable->fv);
if (!mv_is_value_missing (&est[n]->variable->miss, tmp))
{
d = (tmp->f - est[n]->mean);
}
}
}
- read_case = innovations_update_cases (r, c, max_lag);
+ read_case = innovations_update_cases (r, inn_c, max_lag);
}
for (lag = 0; lag <= max_lag; lag++)
{
}
for (lag = 0; lag < max_lag; lag++)
{
- free (c[lag]);
+ free (inn_c[lag]);
}
- free (c);
+ free (inn_c);
+}
+static double
+innovations_convolve (double **theta, struct innovations_estimate *est,
+ int i, int j)
+{
+ int k;
+ double result = 0.0;
+
+ for (k = 0; k < i; k++)
+ {
+ result += theta[i-1][i-k-1] * theta[j-1][j-k-1] * est->scale[k];
+ }
+ return result;
+}
+static void
+innovations_update_scale (struct innovations_estimate *est, double *theta,
+ size_t i)
+{
+ double result = 0.0;
+ size_t j;
+ size_t k;
+
+
+ result = est->cov[0];
+ for (j = 0; j < i; j++)
+ {
+ k = i - j;
+ result -= theta[k] * theta[k] * est->scale[j];
+ }
+ est->scale[i] = result;
+}
+
+static void
+get_coef (size_t n_vars, const struct casefile *cf,
+ 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]));
+
+ }
+ for (n = 0; n < n_vars; n++)
+ {
+ for (i = 0; i < max_lag; i++)
+ {
+ for (j = 0; j < i; j++)
+ {
+ theta[i][j] = 0.0;
+ }
+ }
+ 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);
+ }
+ /* Copy the final row of coefficients into EST->COEFF.*/
+ for (i = 0; i < max_lag; i++)
+ {
+ /*
+ The order of storage here means that the best predicted value
+ for the time series is computed as follows:
+
+ Let X[m], X[m-1],... denote the original series.
+ Let X_hat[0] denote the best predicted value of X[0],
+ X_hat[1] denote the projection of X[1] onto the subspace
+ spanned by {X[0] - X_hat[0]}. Let X_hat[m] denote the
+ projection of X[m] onto the subspace spanned by {X[m-1] - X_hat[m-1],
+ X[m-2] - X_hat[m-2],...,X[0] - X_hat[0]}.
+
+ Then X_hat[m] = est->coeff[m-1] * (X[m-1] - X_hat[m-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]);
+ }
+ }
+ for (i = 0; i < max_lag; i++)
+ {
+ free (theta[i]);
+ }
+ free (theta);
}
-struct innovations_estimate ** pspp_innovations (const struct variable **vars, size_t *n_vars,
- size_t lag, const struct casefile *cf)
+struct innovations_estimate **
+pspp_innovations (const struct variable **vars,
+ size_t n_vars,
+ size_t lag,
+ const struct casefile *cf)
{
struct innovations_estimate **est;
size_t i;
size_t j;
- est = xnmalloc (*n_vars, sizeof *est);
- for (i = 0; i < *n_vars; i++)
+ est = xnmalloc (n_vars, sizeof *est);
+ for (i = 0; i < n_vars; i++)
{
if (vars[i]->type == NUMERIC)
{
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]->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++)
{
}
else
{
- *n_vars--;
+ n_vars--;
/* msg (MW, _("Cannot compute autocovariance for a non-numeric variable %s"), */
/* var_to_string (vars[i])); */
}
}
- /*
- First data pass to get the mean and variance.
- */
- get_mean_variance (*n_vars, cf, est);
- get_covariance (*n_vars, cf, est, lag);
+ get_mean_variance (n_vars, cf, est);
+ get_covariance (n_vars, cf, est, lag);
+ get_coef (n_vars, cf, est, lag);
return est;
}