[R] Automatically extract info from Granger causality output
Pfaff, Bernhard Dr.
Bernhard_Pfaff at fra.invesco.com
Fri Apr 15 10:13:29 CEST 2011
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.
> -----Ursprüngliche Nachricht-----
> 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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> and provide commented, minimal, self-contained, reproducible code.
>
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