From: Jason Stover <jhs@math.gcsu.edu>
Date: Wed, 7 Jun 2006 01:52:48 +0000 (+0000)
Subject: fixed mistakes
X-Git-Tag: v0.6.0~823
X-Git-Url: https://pintos-os.org/cgi-bin/gitweb.cgi?a=commitdiff_plain;h=597402f4808b749094b3f90a96d96adf67e41c5b;p=pspp-builds.git

fixed mistakes
---

diff --git a/src/math/ts/innovations.c b/src/math/ts/innovations.c
index dba44849..3b263bff 100644
--- a/src/math/ts/innovations.c
+++ b/src/math/ts/innovations.c
@@ -38,9 +38,7 @@
 #include <libpspp/compiler.h>
 #include <libpspp/message.h>
 #include <math/coefficient.h>
-#include <math/innovations.h>
-#include <gettext.h>
-#define _(msgid) gettext (msgid)
+#include <math/ts/innovations.h>
 
 static void
 get_mean_variance (size_t n_vars, const struct casefile *cf,
@@ -48,13 +46,10 @@ get_mean_variance (size_t n_vars, const struct casefile *cf,
 		   
 {
   struct casereader *r;
-  struct ccase *c;
-  struct ccase *c2;
+  struct ccase c;
   size_t n;
-  double *x;
   double d;
-  double tmp;
-  double variance;
+  const union value *tmp;
 
   for (n = 0; n < n_vars; n++)
     {
@@ -67,10 +62,10 @@ get_mean_variance (size_t n_vars, const struct casefile *cf,
     {
       for (n = 0; n < n_vars; n++)
 	{
-	  if (!mv_is_value_missing (&v->miss, val))
+	  tmp = case_data (&c, est[n]->variable->fv);
+	  if (!mv_is_value_missing (&(est[n]->variable->miss), tmp))
 	    {
-	      tmp = case_data (&c, est[n]->variable->fv);
-	      d = (tmp - est[n]->mean) / est[n]->n_obs;
+	      d = (tmp->f - 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;
@@ -182,6 +177,7 @@ struct innovations_estimate ** pspp_innovations (const struct variable **vars, s
   struct casereader *r;
   struct ccase *c;
   size_t i;
+  size_t j;
 
   est = xnmalloc (*n_vars, sizeof *est);
   for (i = 0; i < *n_vars; i++)
@@ -202,8 +198,8 @@ struct innovations_estimate ** pspp_innovations (const struct variable **vars, s
       else
 	{
 	  *n_vars--;
-	  msg (MW, _("Cannot compute autocovariance for a non-numeric variable %s"),
-		     var_to_string (vars[i]));
+/* 	  msg (MW, _("Cannot compute autocovariance for a non-numeric variable %s"), */
+/* 		     var_to_string (vars[i])); */
 	}
     }
 
diff --git a/src/math/ts/innovations.h b/src/math/ts/innovations.h
new file mode 100644
index 00000000..5cc6b16c
--- /dev/null
+++ b/src/math/ts/innovations.h
@@ -0,0 +1,43 @@
+/*
+  src/math/time-series/arma/innovations.h
+  
+  Copyright (C) 2006 Free Software Foundation, Inc. Written by Jason H. Stover.
+  
+  This program is free software; you can redistribute it and/or modify it under
+  the terms of the GNU General Public License as published by the Free
+  Software Foundation; either version 2 of the License, or (at your option)
+  any later version.
+  
+  This program is distributed in the hope that it will be useful, but WITHOUT
+  ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
+  FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for
+  more details.
+  
+  You should have received a copy of the GNU General Public License along with
+  this program; if not, write to the Free Software Foundation, Inc., 51
+  Franklin Street, Fifth Floor, Boston, MA 02111-1307, USA.
+ */
+/*
+  Find preliminary ARMA coefficients via the innovations algorithm.
+  Also compute the sample mean and covariance matrix for each series.
+
+  Reference:
+
+  P. J. Brockwell and R. A. Davis. Time Series: Theory and
+  Methods. Second edition. Springer. New York. 1991. ISBN
+  0-387-97429-6. Sections 5.2, 8.3 and 8.4.
+ */
+#ifndef INNOVATIONS_H
+#define INNOVATIONS_H
+#include <math/coefficient.h>
+struct innovations_estimate
+{
+  struct variable *variable;
+  double mean;
+  double variance;
+  double *cov;
+  double n_obs;
+  double max_lag;
+  coefficient *coeff;
+};
+#endif