ERIC: Does S-Plus have Kalman filtering software that would work
with 6 short irregular time series?
Xao Ping: What do your 36 numbers look like? For example, do you
get crudely a straight line with "qqnorm"? If yes, I think "lme" with
"correlation=corCAR1" might give you something useful. I haven't used
"corCAR1", but it looks like that should work. Of course, it would help
to consult Pinheiro and Bates (2000) Mixed-Effects Models in S and
S-Plus (Springer, esp. sec. 5.3). For testing, I think I would want to
use "simulate.lme" as described in Pinheiro and Bates (sec. 2.4), in
part because some of the things you might want to test would have
parameters at a boundary, which would create problems with the usual
asymptotics.
spencer graves
Eric Zivot wrote:
One way to think of the irregular spacing is in terms of missing data.
The true process works on equally spaced data but you ony observe data
on specific dates. An AR type model can be fit using Kalman Filter
techniques that automatically take care of the missing data.
------------------------------------------------------------------------
From: s-news-owner@lists.biostat.wustl.edu
[mailto:s-news-owner@lists.biostat.wustl.edu] On Behalf Of Xao Ping
Sent: Wednesday, June 22, 2005 10:20 AM
To: s-plus user list
Subject: [S] AR for short, not equally spaced TS
Dear All:
I am analyzing a time course microarray experiment. I have only 6 chips
taken in the moments of time 10, 501,2, , 85, 100 (relative units). I am
thinking to apply time series analysis methods, such as AR or ARMA or
ARIMA. I have several questions
1. Is it appropriate at all to think about autoregressive methods when
the TS are not equally spaced? If the answer is "NO", then are there any
alternative approaches?
2. Is it possible to extract any useful information having only 6 data
points?
Any relevant experience or advice are highly appreciated
thank you in advance
Xao Ping
R&R Pharmakinetics
Taiwan
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