On Thu, 9 Sep 2010, John C Frain wrote:
My initial encounter with seasonal adjustment was as a
statistician in the Central Statistics Office in Dublin...
Thanks, John, for presenting the expert's view!
Although I recently conceded to Henrique's request to trim leading
and trailing NAs from the sample passed to X-12-ARIMA, the reason
I hadn't done that before was that I had the idea that x12a could
handle missing values, if they were given as -9999 (or -99999?).
In your previous posting you said,
"While the X12-ARIMA manual states that missing values are not
allowed there are ways around this. If the missing value is
replaced by -99999 then -99999 may be replaced by a value that is
regarded as an outlier and then this may be replace by the
appropriate Reg-ARIMA fitted value for the purpose of estimation
seasonal factors etc. This may require specific X12ARIMA options
to be in effect and running X12-ARIMA outside of Gretl."
This gives me a general notion, but not enough in the way of
specifics to correct my previous (mis-)conception. Do you know of
a specific option that can be passed to x12a to get it to
interpret -99999 as missing? If so, that could easily be added to
gretl's invocation of the program.
As regards gretl native code, as you noted we don't accept
interior missing values for any dynamic time-series estimators.
This is more restrictive than it needs to be: our native Kalman
filter can handle NAs, and so our native AR(I)MA (which uses
Kalman) should also be able to handle them. But so far this
remains on the TODO list (on which there are many other things).
Allin