[Vars-commits] r72 - pkg/man

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

Author: matthieu
Date: 2010-02-13 16:48:53 +0100 (Sat, 13 Feb 2010)
New Revision: 72

Modified:
   pkg/man/causality.Rd
Log:
Man page of causality: add example and few corrections

Modified: pkg/man/causality.Rd
===================================================================
--- pkg/man/causality.Rd	2010-02-13 15:48:50 UTC (rev 71)
+++ pkg/man/causality.Rd	2010-02-13 15:48:53 UTC (rev 72)
@@ -23,7 +23,7 @@
     variable and a warning is printed.}   
   \item{vcov.}{a specification of the covariance matrix of the estimated coefficients. This can be
     specified as a matrix or as a function yielding a matrix when applied to \code{x}.}
-  \item{boot}{Logical. Whether a wild bootstrap procedure should be used to compute the critical  	values. Default is no}
+  \item{boot}{Logical. Whether a wild bootstrap procedure should be used to compute the critical values. Default is no}
   \item{boot.runs}{Number of bootstrap replications if boot=TRUE}
 }
 
@@ -71,9 +71,12 @@
   \eqn{\chi^2(N)}.
   
   Fot the Granger causality test, a robust covariance-matrix estimator can be 
-  used through argument \code{vcov.} It can be either a pre-computed matrix or
+  used in case of heteroskedasticity through argument \code{vcov.} It can be either a pre-computed matrix or
   a function for extracting the covariance matrix. See \code{\link[sandwich]{vcovHC}}
-  from package \pkg{sandwich} for further details. A wild bootstrap computation (imposing the restricted model as null) of the p values is available through argument \code{boot}. 
+  from package \pkg{sandwich} for further details. 
+
+  A wild bootstrap computation (imposing the restricted model as null)
+  of the p values is available through argument \code{boot} and \code{boot.runs} following Hafner and Herwartz (2009). 
 }
 
 \value{
@@ -122,7 +125,13 @@
 \examples{
 data(Canada)
 var.2c <- VAR(Canada, p = 2, type = "const")
-causality(var.2c, cause = "e")
+causality(var.2c, cause = "e")
+
+#use a robust HC variance-covariance matrix for the Granger test:
+causality(var.2c, cause = "e", vcov.=vcovHC(var.2c))
+
+#use a wild-bootstrap procedure to for the Granger test
+\dontrun{causality(var.2c, cause = "e", boot=TRUE, boot.runs=1000)}
 }
 
 \keyword{regression}