Automatically extract info from Granger causality output

str(Count)

Dear Ivan,

first, it would pay-off in terms of readability to employ line breaks and second to provide a reproducable code snippet and third which package you have used. Now to your questions:
1) What happens if you provide colnames for your objects?
2) What happens if you omit the $ after count?

Best,
Bernhard

ps: the function seems to have been ported from the package 'vars'. In this package the function causality() is included which returns a named list with elements of class htest.

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Von: r-help-bounces at r-project.org
[mailto:r-help-bounces at r-project.org] Im Auftrag von ivan
Gesendet: Donnerstag, 14. April 2011 19:37
An: r-help at r-project.org
Betreff: [R] Automatically extract info from Granger causality output

Dear Community,

this is my first programming in R and I am stuck with a
problem. I have the following code which automatically
calculates Granger causalities from a variable, say e.g. "bs"
as below, to all other variables in the data frame:

log.returns<-as.data.frame( lapply(daten, function(x)
diff(log(ts(x))))) y1<-log.returns$bs
y2<- log.returns[,!(names(log.returns) %in% "bs")]
Granger<- function(y1,y2) {models=lapply(y2, function(x)
VAR(cbind(x,y1),ic="SC") ); results=lapply(models,function(x)
causality(x,cause="y1")); print(results)}
Count<-Granger(y1,y2)

which produces the following output (I have printed only part
of it (for Granger causality of bs on ml)):

$ml
$ml$Granger

? ? ? ? Granger causality H0: y1 do not Granger-cause x

data: ?VAR object x
F-Test = 0.2772, df1 = 1, df2 = 122, p-value = 0.5995


$ml$Instant

? ? ? ? H0: No instantaneous causality between: y1 and x

data: ?VAR object x
Chi-squared = 19.7429, df = 1, p-value = 8.859e-06

My questions:

1)How can I edit the function above so that the output writes: Granger
causality H0: bs do not Granger-cause ml ? rather than ?Granger
causality H0: y1 do not Granger-cause x?

2) I want to extract the p-values of the tests into a data
frame for instance. The problem is that the output has a 3
layer structure.
Thus, for the above p-value I need to write count$ml$Granger$p.value.
I thought of a loop of something like for(i in
1:length(count)) {z=count$[[i]]$Granger$p.value} but it didn't work.

Thank you very much for your help.

Best Regards.

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