X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=blobdiff_plain;f=src%2Fmath%2Fts%2Finnovations.c;h=4fc48c575b81e461123ce4ee93fd6690a59011da;hb=d94b00b8d019bb2fda05366a2e86505fff13dbe3;hp=43d86ec1677c8c9bb381f59b23109da8f09940f5;hpb=29e712969d0d5bc1ee20458309dee7df2c38f1ae;p=pspp-builds.git

diff --git a/src/math/ts/innovations.c b/src/math/ts/innovations.c
index 43d86ec1..4fc48c57 100644
--- a/src/math/ts/innovations.c
+++ b/src/math/ts/innovations.c
@@ -1,5 +1,5 @@
 /*
-  src/math/time-series/arma/innovations.c
+  src/math/ts/innovations.c
   
   Copyright (C) 2006 Free Software Foundation, Inc. Written by Jason H. Stover.
   
@@ -30,183 +30,273 @@
 
 #include <gsl/gsl_matrix.h>
 #include <gsl/gsl_vector.h>
-#include <math.h>
+#include <gsl/gsl_math.h>
 #include <stdlib.h>
-#include <data/case.h>
-#include <data/casefile.h>
 #include <libpspp/alloc.h>
 #include <libpspp/compiler.h>
-#include <libpspp/message.h>
 #include <math/coefficient.h>
 #include <math/ts/innovations.h>
 
 static void
-get_mean_variance (size_t n_vars, const struct casefile *cf,
+get_mean_variance (const gsl_matrix *data,
 		   struct innovations_estimate **est)
 		   
 {
-  struct casereader *r;
-  struct ccase c;
   size_t n;
+  size_t i;
   double d;
-  const union value *tmp;
+  double tmp;
 
-  for (n = 0; n < n_vars; n++)
+  for (n = 0; n < data->size2; n++)
     {
       est[n]->n_obs = 2.0;
       est[n]->mean = 0.0;
       est[n]->variance = 0.0;
     }
-  for (r = casefile_get_reader (cf); casereader_read (r, &c);
-       case_destroy (&c))
+  for (i = 0; i < data->size1; i++)
     {
-      for (n = 0; n < n_vars; n++)
+      for (n = 0; n < data->size2; n++)
 	{
-	  tmp = case_data (&c, est[n]->variable->fv);
-	  if (!mv_is_value_missing (&(est[n]->variable->miss), tmp))
+	  tmp = gsl_matrix_get (data, i, n);
+	  if (!gsl_isnan (tmp))
 	    {
-	      d = (tmp->f - est[n]->mean) / est[n]->n_obs;
+	      d = (tmp - est[n]->mean) / est[n]->n_obs;
 	      est[n]->mean += d;
 	      est[n]->variance += est[n]->n_obs * est[n]->n_obs * d * d;
 	      est[n]->n_obs += 1.0;
 	    }
 	}
     }
-  for (n = 0; n < n_vars; n++)
+  for (n = 0; n < data->size2; n++)
     {
       /* Maximum likelihood estimate of the variance. */
       est[n]->variance /= est[n]->n_obs;
     }
 }
 
-/*
-  Read the first MAX_LAG cases.
- */
-static bool
-innovations_init_cases (struct casereader *r, struct ccase **c, size_t max_lag)
-{
-  bool value = true;
-  size_t lag = 0;
-
-  while (value && lag < max_lag)
-    {
-      lag++;
-      value = casereader_read (r, c[lag]);
-    }
-  return value;
-}
-
-/*
-  Read one case and update C, which contains the last MAX_LAG cases.
- */
-static bool
-innovations_update_cases (struct casereader *r, struct ccase **c, size_t max_lag)
-{
-  size_t lag;
-  bool value = false;
-  
-  for (lag = 0; lag < max_lag - 1; lag++)
-    {
-      c[lag] = c[lag+1];
-    }
-  value = casereader_read (r, c[lag]);
-  return value;
-}
-static void
-get_covariance (size_t n_vars, const struct casefile *cf, 
+static int
+get_covariance (const gsl_matrix *data, 
 		struct innovations_estimate **est, size_t max_lag)
 {
-  struct casereader *r;
-  struct ccase **c;
   size_t lag;
-  size_t n;
-  bool read_case = false;
-  double d;
+  size_t j;
+  size_t i;
   double x;
-  const union value *tmp;
-  const union value *tmp2;
+  double y;
+  int rc = 1;
 
-  c = xnmalloc (max_lag, sizeof (*c));
+  assert (data != NULL);
+  assert (est != NULL);
   
-  for (lag = 0; lag < max_lag; lag++)
-    {
-      c[lag] = xmalloc (sizeof *c[lag]);
-    }
-
-  r = casefile_get_reader (cf);
-  read_case = innovations_init_cases (r, c, max_lag);
-
-  while (read_case)
+  for (i = 0; i < data->size1; i++)
     {
-      for (n = 0; n < n_vars; n++)
+      for (j = 0; j < data->size2; j++)
 	{
-	  tmp2 = case_data (c[0], est[n]->variable->fv);
-	  if (!mv_is_value_missing (&est[n]->variable->miss, tmp2))
+	  x = gsl_matrix_get (data, i, j);
+
+	  if (!gsl_isnan (x))
 	    {
-	      x = tmp2->f - est[n]->mean;
-	      for (lag = 1; lag <= max_lag; lag++)
+	      x -= est[j]->mean;
+	      for (lag = 1; lag <= max_lag && lag < (data->size1 - i); lag++)
 		{
-		  tmp = case_data (c[lag], est[n]->variable->fv);
-		  if (!mv_is_value_missing (&est[n]->variable->miss, tmp))
+		  y = gsl_matrix_get (data, i + lag, j);
+		  if (!gsl_isnan (y))
 		    {
-		      d = (tmp->f - est[n]->mean);
-		      *(est[n]->cov + lag) += d * x;
+		      y -= est[j]->mean;
+		      *(est[j]->cov + lag - 1) += y * x;
+		      est[j]->n_obs += 1.0;
 		    }
 		}
 	    }
 	}
-      read_case = innovations_update_cases (r, c, max_lag);
     }
-  for (lag = 0; lag <= max_lag; lag++)
+  for (lag = 1; lag <= max_lag; lag++)
     {
-      for (n = 0; n < n_vars; n++)
+      for (j = 0; j < data->size2; j++)
 	{
-	  *(est[n]->cov + lag) /= (est[n]->n_obs - lag);
+	  *(est[j]->cov + lag) /= (est[j]->n_obs - lag);
 	}
     }
-  for (lag = 0; lag < max_lag; lag++)
+  return rc;
+}
+static double
+innovations_convolve (double **theta, struct innovations_estimate *est,
+		      int i, int j)
+{
+  int k;
+  double result = 0.0;
+
+  for (k = 0; k < j; k++)
     {
-      free (c[lag]);
+      result += theta[i-1][i-k-1] * theta[j][j-k-1] * est->scale[k];
     }
-  free (c);
+  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;
 
-struct innovations_estimate ** pspp_innovations (const struct variable **vars, size_t *n_vars,
-						 size_t lag, const struct casefile *cf)
+
+  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;
+}
+static void
+init_theta (double **theta, size_t max_lag)
 {
-  struct innovations_estimate **est;
   size_t i;
   size_t j;
 
-  est = xnmalloc (*n_vars, sizeof *est);
-  for (i = 0; i < *n_vars; i++)
+  for (i = 0; i < max_lag; i++)
     {
-      if (vars[i]->type == NUMERIC)
+      for (j = 0; j <= i; j++)
 	{
-	  est[i] = xmalloc (sizeof **est);
-	  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]->coeff = xnmalloc (lag, sizeof (*est[i]->coeff));
-	  for (j = 0; j < lag; j++)
-	    {
-	      est[i]->coeff[j] = xmalloc (sizeof (*(est[i]->coeff + 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;
+
+  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];
 	}
-      else
+      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 i;
+  size_t n;
+  double **theta;
+
+  theta = xnmalloc (max_lag, sizeof (*theta));
+  for (i = 0; i < max_lag; i++)
+    {
+      theta[i] = xnmalloc (max_lag, sizeof (**(theta + i)));
+    }
+
+  for (n = 0; n < data->size2; n++)
+    {
+      init_theta (theta, max_lag);
+      innovations_update_scale (est[n], theta[0], 0);
+      innovations_update_coeff (theta, est[n], max_lag);
+      /* Copy the final row of coefficients into EST->COEFF.*/
+      for (i = 0; i < max_lag; i++)
 	{
-	  *n_vars--;
-/* 	  msg (MW, _("Cannot compute autocovariance for a non-numeric variable %s"), */
-/* 		     var_to_string (vars[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]);
 	}
     }
 
-  /*
-    First data pass to get the mean and variance.
-   */
-  get_mean_variance (*n_vars, cf, est);
-  get_covariance (*n_vars, cf, est, lag);
+  for (i = 0; i < max_lag; i++)
+    {
+      free (theta[i]);
+    }
+  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, 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;
+
+  est = xnmalloc (data->size2, sizeof *est);
+  for (i = 0; i < data->size2; i++)
+    {
+      est[i] = xmalloc (sizeof *est[i]);
+/*       est[i]->variable = vars[i]; */
+      innovations_struct_init (est[i], lag);
+    }
+
+  get_mean_variance (data, est);
+  get_covariance (data, est, lag);
+  get_coef (data, est, lag);
   
   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);
+}