[Vinecopula-commits] r32 - in pkg: R man

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

Author: ulf
Date: 2013-10-17 15:14:59 +0200 (Thu, 17 Oct 2013)
New Revision: 32

Modified:
   pkg/R/RVineTreePlot.r
   pkg/man/RVineGofTest.Rd
Log:
Fehler behoben in der RVineTreePlot.r und die Familien definiert bei den GOF

Modified: pkg/R/RVineTreePlot.r
===================================================================
--- pkg/R/RVineTreePlot.r	2013-10-11 14:32:57 UTC (rev 31)
+++ pkg/R/RVineTreePlot.r	2013-10-17 13:14:59 UTC (rev 32)
@@ -141,12 +141,16 @@
   for(j in 1:(d-2)) edgelist[[2]][j,] = c(paste(edges[[2]][j,1,],collapse=","),paste(edges[[2]][j,2,],collapse=","))
 
   # separate conditioned and conditioning sets
-  for(i in 3:(d-1)){
-    for(j in 1:(d-i)){
-      edgelist[[i]][j,1] = paste(paste(edges[[i]][j,1,1:2],collapse=","),paste(edges[[i]][j,1,3:i],collapse=","),sep="|")
-      edgelist[[i]][j,2] = paste(paste(edges[[i]][j,2,1:2],collapse=","),paste(edges[[i]][j,2,3:i],collapse=","),sep="|")
-    }
-  }
+  if(d>3)
+  {
+	for(i in 3:(d-1)){
+		for(j in 1:(d-i))
+		{
+			edgelist[[i]][j,1] = paste(paste(edges[[i]][j,1,1:2],collapse=","),paste(edges[[i]][j,1,3:i],collapse=","),sep="|")
+			edgelist[[i]][j,2] = paste(paste(edges[[i]][j,2,1:2],collapse=","),paste(edges[[i]][j,2,3:i],collapse=","),sep="|")
+		}
+	}
+	}
   
   
 

Modified: pkg/man/RVineGofTest.Rd
===================================================================
--- pkg/man/RVineGofTest.Rd	2013-10-11 14:32:57 UTC (rev 31)
+++ pkg/man/RVineGofTest.Rd	2013-10-17 13:14:59 UTC (rev 32)
@@ -13,7 +13,8 @@
 
 \arguments{
   \item{data}{An N x d data matrix (with uniform margins).} 
-  \item{RVM}{\code{\link{RVineMatrix}} objects of the R-vine model under the null hypothesis.}
+  \item{RVM}{\code{\link{RVineMatrix}} objects of the R-vine model under the null hypothesis. \cr
+  Note that the pair-copula families in the R-vine Matrix object have to be a member of the vector \code{(0,1:6,13,14,16,23,24,26,33,34,36)}}
   \item{method}{A string indicating the goodness-of-fit method:\cr
 		\code{"White"} = goodness-of-fit test based on White's information matrix equality (default) \cr
 		\code{"IR"} = goodness-of-fit test based on the information ratio \cr