[Vinecopula-commits] r9 - in pkg: inst man

[noreply at r-forge.r-project.org]

Author: ulf
Date: 2013-04-22 09:30:41 +0200 (Mon, 22 Apr 2013)
New Revision: 9

Modified:
   pkg/inst/ChangeLog
   pkg/man/RVineClarkeTest.Rd
   pkg/man/RVineVuongTest.Rd
Log:
Bsp angepasst und den ChangeLog

Modified: pkg/inst/ChangeLog
===================================================================
--- pkg/inst/ChangeLog	2013-04-18 16:10:29 UTC (rev 8)
+++ pkg/inst/ChangeLog	2013-04-22 07:30:41 UTC (rev 9)
@@ -3,14 +3,20 @@
 Ulf Schepsmeier, Jakob Stoeber and Eike Christian Brechmann <VineCopula at ma.tum.de>
 
 
-Version 1.1-2 (March, 13, 2013)
+Version 1.1-2 (April, 22, 2013)
 
 - Additional validy check of the R-vine matrix  in RVineMatrix (Code provided by Harry Joe)
 
 - New bivariate copula: Reflection asymmetric Archimedean copula
-  In our functions it is "family=41", 51, 61, and 71 for the rotated versions.
+  In our functions it is "family=41", and 51, 61, and 71 for the rotated versions.
   So far only implemented in some bivariate functions (not documented so far; experimental)
+
+- New author: Benedikt Gräler  
   
+- Bug fix:
+  * New (correct) examples for the Clarke and Vuong test
+  * Fixed memory problem in the C-function ktau (TauMatrix)
+  
 
 Version 1.1-1 (February 7, 2013)
 

Modified: pkg/man/RVineClarkeTest.Rd
===================================================================
--- pkg/man/RVineClarkeTest.Rd	2013-04-18 16:10:29 UTC (rev 8)
+++ pkg/man/RVineClarkeTest.Rd	2013-04-22 07:30:41 UTC (rev 9)
@@ -63,45 +63,22 @@
 
 
 \examples{
-# define first 5-dimensional RVineMatrix object
-Matrix1 = c(5,2,3,1,4,0,2,3,4,1,0,0,3,4,1,0,0,0,4,1,0,0,0,0,1)
-Matrix1 = matrix(Matrix1,5,5)
+\dontrun{
+# load data set
+data(daxreturns)
 
-family1 = c(0,1,3,4,4,0,0,3,4,1,0,0,0,4,1,0,0,0,0,3,0,0,0,0,0)
-family1 = matrix(family1,5,5)
+# select the R-vine structure, families and parameters
+RVM = RVineStructureSelect(daxreturns[,1:5],c(1:6))
 
-par1 = c(0,0.2,0.9,1.5,3.9,0,0,1.1,1.6,0.9,0,0,0,1.9,0.5,
-         0,0,0,0,4.8,0,0,0,0,0)
-par1 = matrix(par1,5,5)
+# select the C-vine structure, families and parameters
+CVM = RVineStructureSelect(daxreturns[,1:5],c(1:6),type="CVine")
 
-RVM1 = RVineMatrix(Matrix=Matrix1,family=family1,par=par1,
-                   par2=matrix(0,5,5),names=c("V1","V2","V3","V4","V5"))
-                  
-# define second 5-dimensional RVineMatrix object
-Matrix2 = c(5,4,3,2,1,0,4,3,2,1,0,0,3,2,1,0,0,0,2,1,0,0,0,0,1)
-Matrix2 = matrix(Matrix2,5,5)
-
-family2 = c(0,3,1,3,2,0,0,1,5,3,0,0,0,2,3,0,0,0,0,1,0,0,0,0,0)
-family2 = matrix(family2,5,5)
-
-par2 = c(0,0.8,0.3,1.5,0.8,0,0,-0.4,1.6,1.2,0,0,0,-0.4,1.5,
-         0,0,0,0,0.6,0,0,0,0,0)
-par2 = matrix(par2,5,5)
-
-nu2 = c(0,0,0,0,5,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0)
-nu2 = matrix(nu2,5,5)
-
-RVM2 = RVineMatrix(Matrix=Matrix2,family=family2,par=par2,par2=nu2,
-                   names=c("V1","V2","V3","V4","V5"))                  
-
-# simulate a sample of size 300 from the first R-vine copula model
-simdata = RVineSim(300,RVM1)
-
-# compare the two models based on this sample
-clarke = RVineClarkeTest(simdata,RVM1,RVM2)
+# compare the two models based on the data
+clarke = RVineClarkeTest(daxreturns[,1:5],RVM,CVM)
 clarke$statistic
 clarke$statistic.Schwarz
 clarke$p.value
 clarke$p.value.Schwarz
 }
+}
 

Modified: pkg/man/RVineVuongTest.Rd
===================================================================
--- pkg/man/RVineVuongTest.Rd	2013-04-18 16:10:29 UTC (rev 8)
+++ pkg/man/RVineVuongTest.Rd	2013-04-22 07:30:41 UTC (rev 9)
@@ -68,45 +68,22 @@
 
 
 \examples{
-# define first 5-dimensional RVineMatrix object
-Matrix1 = c(5,2,3,1,4,0,2,3,4,1,0,0,3,4,1,0,0,0,4,1,0,0,0,0,1)
-Matrix1 = matrix(Matrix1,5,5)
+\dontrun{
+# load data set
+data(daxreturns)
 
-family1 = c(0,1,3,4,4,0,0,3,4,1,0,0,0,4,1,0,0,0,0,3,0,0,0,0,0)
-family1 = matrix(family1,5,5)
+# select the R-vine structure, families and parameters
+RVM = RVineStructureSelect(daxreturns[,1:5],c(1:6))
 
-par1 = c(0,0.2,0.9,1.5,3.9,0,0,1.1,1.6,0.9,0,0,0,1.9,0.5,
-         0,0,0,0,4.8,0,0,0,0,0)
-par1 = matrix(par1,5,5)
+# select the C-vine structure, families and parameters
+CVM = RVineStructureSelect(daxreturns[,1:5],c(1:6),type="CVine")
 
-RVM1 = RVineMatrix(Matrix=Matrix1,family=family1,par=par1,
-                   par2=matrix(0,5,5),names=c("V1","V2","V3","V4","V5"))
-                  
-# define second 5-dimensional RVineMatrix object
-Matrix2 = c(5,4,3,2,1,0,4,3,2,1,0,0,3,2,1,0,0,0,2,1,0,0,0,0,1)
-Matrix2 = matrix(Matrix2,5,5)
-
-family2 = c(0,3,1,3,2,0,0,1,5,3,0,0,0,2,3,0,0,0,0,1,0,0,0,0,0)
-family2 = matrix(family2,5,5)
-
-par2 = c(0,0.8,0.3,1.5,0.8,0,0,-0.4,1.6,1.2,0,0,0,-0.4,1.5,
-         0,0,0,0,0.6,0,0,0,0,0)
-par2 = matrix(par2,5,5)
-
-nu2 = c(0,0,0,0,5,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0)
-nu2 = matrix(nu2,5,5)
-
-RVM2 = RVineMatrix(Matrix=Matrix2,family=family2,par=par2,par2=nu2,
-                   names=c("V1","V2","V3","V4","V5"))                  
-
-# simulate a sample of size 300 from the first R-vine copula model
-simdata = RVineSim(300,RVM1)
-
-# compare the two models based on this sample
-vuong = RVineVuongTest(simdata,RVM1,RVM2)
+# compare the two models based on the data
+vuong = RVineVuongTest(daxreturns[,1:5],RVM,CVM)
 vuong$statistic
 vuong$statistic.Schwarz
 vuong$p.value
 vuong$p.value.Schwarz
 }
+}