[R] How to implement an iterative unit root test
abunn at whrc.org
Thu Apr 6 04:02:31 CEST 2006
Does this get you started?
foo <- matrix(rnorm(1000),ncol=10,nrow=100)
bar <- apply(foo,2,adf.test)
sapply(bar, "[[", "statistic")
sapply(bar, "[[", "p.value")
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
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
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?
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