For not equally spaced TS, you may consider continous model fitting. I have
developed an R package. See references and the program at people.smu.edu/zhuw.
Hope this helps.
Regards,
Zhu
-----Original Message-----
From: s-news-owner@lists.biostat.wustl.edu on behalf of Spencer Graves
Sent: Wed 6/22/2005 1:00 PM
To: Eric Zivot
Cc: 'Xao Ping'; 's-plus user list'
Subject: Re: [S] AR for short, not equally spaced TS
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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--
Spencer Graves, PhD
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