[R] How to implement an iterative unit root test

[Gabor Grothendieck]

That's a warning, not an error.   I get it or don't get it with and
without rollFun in the same circumstances. If you have a situation
where that is not so please provide it in a reproducible way.

> library(fMultivar)
> set.seed(1)
> x <- rnorm(25)

> # these give no warning
> rollFun(x, 15, FUN = function(x) adf.test(x)$p.value)
 [1] 0.1207730 0.3995849 0.3261577 0.4733004 0.5776586 0.6400228 0.6758550
 [8] 0.6897812 0.3792858 0.6587171 0.5675147
> adf.test(x[1:15])$statistic
Dickey-Fuller
    -3.185471

> # these give warning
> rollFun(x, 10, FUN = function(x) adf.test(x)$p.statistic)
NULL
Warning messages:
1: p-value smaller than printed p-value in: adf.test(x)
2: p-value smaller than printed p-value in: adf.test(x)
3: p-value smaller than printed p-value in: adf.test(x)
4: p-value smaller than printed p-value in: adf.test(x)
5: p-value greater than printed p-value in: adf.test(x)
6: p-value greater than printed p-value in: adf.test(x)
7: p-value greater than printed p-value in: adf.test(x)
> # this gives warning
> adf.test(x[1:10])$statistic
Dickey-Fuller
    -5.316689
Warning message:
p-value smaller than printed p-value in: adf.test(x[1:10])





On 4/8/06, Bernd Dittmann <herrdittmann at yahoo.co.uk> wrote:
> 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 <herrdittmann at yahoo.co.uk> 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:
> r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch]
> On Behalf Of Bernd Dittmann
Sent: Wednesday, April 05, 2006 8:58 PM
To:
> r-help at stat.math.ethz.ch
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

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