Thank you for the suggestion.
I ran it and oddly enough I am getting contradicting results:
> rollFun(x[1:100], 10, FUN = function(x) adfTest(x)$statistic)
NULL
Warning messages:
1: p-value smaller than printed p-value in: adfTest(x)
.......
.......
.......
These error messages appear for each single calculation.
However, performing the unit root test for that very interval (although
not repetitive) the results are:
> adfTest(x[1:100])
Title:
Augmented Dickey-Fuller Test
Test Results:
PARAMETER:
Lag Order: 1
STATISTIC:
Dickey-Fuller: -0.1627
P VALUE:
0.5612
Description:
Sat Apr 08 19:11:40 2006
I checked with the help pages of the adfTest and fMultivar, but can
simply not figure out why I am receiving these error messages above.
How could I fix this?
Many thanks!
Sincerely,
Bernd Dittmann
Gabor Grothendieck schrieb:
> Try this:
>
>
>> library(fMultivar)
>> set.seed(1)
>> x <- rnorm(25)
>> rollFun(x, 15, FUN = function(x) adf.test(x)$p.value)
>>
> [1] 0.1207730 0.3995849 0.3261577 0.4733004 0.5776586 0.6400228 0.6758550
> [8] 0.6897812 0.3792858 0.6587171 0.5675147
>
>> rollFun(x, 15, FUN = function(x) adf.test(x)$statistic)
>>
> [1] -3.185471 -2.453590 -2.646336 -2.260086 -1.986146 -1.822440 -1.728381
> [8] -1.691824 -2.506875 -1.773368 -2.012774
>
> Also, rapply in the zoo package and running in the gtools package are two
> other
> rolling routines.
>
> On 4/8/06, Bernd Dittmann <[EMAIL PROTECTED]> wrote:
>
>> Thank you for your suggestion, Andy.
>>
>> Luckily, the fMultivar package has already implemented such a "rolling"
>> function: "rollFun".
>>
>> Thus I tried the following:
>>
>>
>> myfunction <- function(x, n = 5)
>> {
>> rollFun(x = x, n = n, FUN = adfTest)
>> }
>>
>>
>> This however does not return the tau values (or alternatively, the
>> p.values) I am looking for.
>> How do I need to define the function FUN to obtain these values?
>>
>>
>> Many thanks!
>>
>> Sincerely,
>>
>> Bernd
>>
>>
>>
>> Andy Bunn schrieb:
>>
>>> Does this get you started?
>>>
>>> library(tseries)
>>> ?adf.test
>>> foo <- matrix(rnorm(1000),ncol=10,nrow=100)
>>> bar <- apply(foo,2,adf.test)
>>> sapply(bar, "[[", "statistic")
>>> sapply(bar, "[[", "p.value")
>>>
>>>
>>> HTH, Andy
>>>
>>> -----Original Message-----
>>> From: [EMAIL PROTECTED]
>>> [mailto:[EMAIL PROTECTED] On Behalf Of Bernd Dittmann
>>> Sent: Wednesday, April 05, 2006 8:58 PM
>>> To: [email protected]
>>> Subject: [R] How to implement an iterative unit root test
>>>
>>>
>>> Hello,
>>>
>>> How can an interative unit root test be implemented in R?
>>> More specifically, given a time series, I wish to perform the Dickey
>>> Fuller Test on a daily basis for say the last 100 observations. It would
>>> be interative in the sense that this test would be repeated each day for
>>> the last 100 observations.
>>> Given the daily Dickey Fuller estimates of delta for the autoregressive
>>> process
>>>
>>> d(Y(t)) = delta * Y(t-1) + u(t)
>>>
>>> , the significance of delta would be computed. If possible, I would like
>>> to extract that value and record it in a table, that is a table
>>> containing the tau-values of a each day's calculations.
>>>
>>>
>>> How can such a test be done in R? More specifically, how can it be
>>> programmed to iteratively perform the test and also how to extract the
>>> t-values on a daily basis?
>>>
>>>
>>> Thank you.
>>>
>>> Sincerely,
>>>
>>> Bernd Dittmann
>>>
>>> ______________________________________________
>>> [email protected] mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide!
>>> http://www.R-project.org/posting-guide.html
>>>
>>>
>>>
>>>
>> ______________________________________________
>> [email protected] mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
>>
>>
>
>
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