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=131284459096b2056b79c86e92b3b290c09bfea4;hpb=4dc2ebcfd1a113b25f6997ff3b66fa52ac41158b;p=pspp-builds.git

diff --git a/src/math/ts/innovations.c b/src/math/ts/innovations.c
index 13128445..4fc48c57 100644
--- a/src/math/ts/innovations.c
+++ b/src/math/ts/innovations.c
@@ -97,20 +97,20 @@ get_covariance (const gsl_matrix *data,
 	  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++)
 	{
@@ -126,9 +126,9 @@ innovations_convolve (double **theta, struct innovations_estimate *est,
   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;
 }
@@ -141,53 +141,67 @@ innovations_update_scale (struct innovations_estimate *est, double *theta,
   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;
+
+  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 (max_lag, 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++)
 	{
@@ -213,6 +227,7 @@ get_coef (const gsl_matrix *data,
 	  pspp_coeff_set_estimate (est[n]->coeff[i], theta[max_lag - 1][i]);
 	}
     }
+
   for (i = 0; i < max_lag; i++)
     {
       free (theta[i]);
@@ -220,27 +235,37 @@ get_coef (const gsl_matrix *data,
   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;
-  size_t j;
 
   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;
-      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++)
-	{
-	  est[i]->coeff[j] = xmalloc (sizeof (*(est[i]->coeff + j)));
-	}
+      innovations_struct_init (est[i], lag);
     }
 
   get_mean_variance (data, est);
@@ -249,3 +274,29 @@ pspp_innovations (const gsl_matrix *data, size_t 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);
+}