[R] Automatically extract info from Granger causality output

[ivan]

Dear Bernhard,

thank you very much for the response. Yes, I am using the packsges
"vars" with fuchrions VAR() and causality().

1)Giving colnames to the objects does unfortunately not  change anything.

2) I am not sure if I understood you right. Did you mean to insert
Countml$Granger$p.value rather than  Count$ml$Granger$p.value? This
returns: Error: Object 'Countms' not found.

By the way, str(Count) produces the following:

> str(Count)
List of 4
 $ ml:List of 2
  ..$ Granger:List of 5
  .. ..$ statistic: num [1, 1] 0.277
  .. .. ..- attr(*, "names")= chr "F-Test"
  .. ..$ parameter: Named num [1:2] 1 122
  .. .. ..- attr(*, "names")= chr [1:2] "df1" "df2"
  .. ..$ p.value  : num [1, 1] 0.6
  .. ..$ method   : chr "Granger causality H0: y1 do not Granger-cause x"
  .. ..$ data.name: chr "VAR object x"
  .. ..- attr(*, "class")= chr "htest"
  ..$ Instant:List of 5
  .. ..$ statistic: num [1, 1] 19.7
  .. .. ..- attr(*, "names")= chr "Chi-squared"
  .. ..$ parameter: Named int 1
  .. .. ..- attr(*, "names")= chr "df"
  .. ..$ p.value  : num [1, 1] 8.86e-06
  .. ..$ method   : chr "H0: No instantaneous causality between: y1 and x"
  .. ..$ data.name: chr "VAR object x"
  .. ..- attr(*, "class")= chr "htest"
 $ jp:List of 2
.
.
.
.

Best Regards,

Ivan

On Fri, Apr 15, 2011 at 10:13 AM, Pfaff, Bernhard Dr.
<Bernhard_Pfaff at fra.invesco.com> wrote:
> 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.
>>
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
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