```Date: Fri, 22 Sep 2006 06:50:00 -0500 Reply-To: dmka Sender: "SAS(r) Discussion" From: dmka Subject: Re: Modelling several time series together using Proc Mixed? Content-Type: text/plain; charset="Windows-1252" Hi All: David and all, here is a clarification of my problem: Chen presented the problem below. I would like to follow up on this issue: First, can this problem be modeled a longitudinal/panel/repeated measures problem? Second, suppose I have developed this model and have a new data set say observed only at time 1 for each ID and would like to forecast the price for each id say over 10 time periods, Is this feasible? If so how? I have a date set which looks like this( I made up the data) ID Time Price 1 1 10 1 2 11 ...... 1 100 150 2 1 9 2 2 10 ........ 2 100 189 ......... 50 1 11 ....... 50 100 190 I want to predict the value at time 101 for each different ID. Obviously I can model 50 independent time series. My questions are that 1. Is it possible that I can treat this data as repeated measurement and use Proc Mixed to build one whole model. 2. If so, how can I write the formula? Proc Mixed data=test; class ID; model Price = Time ID; repeated time / subject=ID; I just want to catch the interaction between different IDs. But I am not sure that Mixed model can do that. I just began to learn the mixed model stuff. So I can easily make mistakes on basic concepts. Thanks Ming ----- Original Message ----- From: "David L Cassell" To: Sent: Friday, September 22, 2006 12:37 AM Subject: Re: Modelling several time series together using Proc Mixed? > djrk0003@COMCAST.NET wrote: > > > >Chen presented the problem below. I would like to follow up on this issue, > >but in a slightly different direction. Suppose, I have a new data set that > >I > >need to score used the model developed below. For the new data set, I would > >like to forest for each ID over a 72 month period. Is this feasible? If so > >how? > > > >Thanks, > > > >Doyle. > > Are you saying that you want to create an entire new data set based > on *no* values from the given ID? That does not sound reasonable. > In a time series, you need at least *some* starting values for > autoregressive > models, and at least *some* starting error terms for moving average > models, and all of the above in ARIMA(p,d,q) models where p and q are > greater than 0. > > Are you going to have some starting values? Are you going to have > a model from PROC AUTOREG to use to predict some expected values > based on a set of regressors? > > Without some more detail, I can't help you much. > > David > -- > David L. Cassell > mathematical statistician > Design Pathways > 3115 NW Norwood Pl. > Corvallis OR 97330 > > _________________________________________________________________ > Add fun gadgets and colorful themes to express yourself on Windows Live > Spaces > http://clk.atdmt.com/MSN/go/msnnkwsp0070000001msn/direct/01/?href=http://www.get.live.com/spaces/features ```

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