Hi Erin, 

1) My guess as to the best way forward would be to use the sequential numbering as the "ts" variable (1-180) and then include indicator variables for months. That would pick up both multi-year trends and it would also pick up seasonal variation. 

2) The only special thing to consider with TS data is that because there is no cross-sectional variable, you can't interact the trends with the cross section (so intercs argument must be FALSE). 

Cheers,
Matt

~~~~~~~~~~~
Matthew Blackwell
Assistant Professor of Government
Harvard University
url: http://www.mattblackwell.org

On Tue, Mar 31, 2015 at 10:53 AM, Graham, Erin <Erin.Graham@oregonstate.edu> wrote:

Amelia users,

 

My data set consists of several environmental predictor variables, each of which are time series with seasonal and trend components. These are monthly values taken over 15 years. I have been experimenting with Amelia and have read the referenced papers and documentation, but two questions remain:

 

1) What is the best way to indicate the "ts" component? If this is monthly, should I assign sequential numbers to my "Month" column (1-180) indicating 12 months X 15 years and leave "Year" out of the analysis, or should I simply number my months 1-12 for each year and again only select "Month" for ts? If there is both a seasonal and a trend component to the data, will it be captured using either of these methods?

 

2) All of my variables (both independent and dependent) are time series, and all have missing values. If I do nothing to the data, except for maybe simple transformations to a few variables to better approach normality, are there any major precautions to imputing ts data from all ts data? Of course, I will experiment with polytime, splinetime, lags, etc.

 

Thank you for your help.

 

Regards,

Erin Graham


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