Re: AR for short, not equally spaced TS

["Eric Zivot" <ezivot@u.washington.edu>]

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.

 

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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 1,2, 10, 50, 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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