Paolo,
á
It is hard to say without the data. I suggest you to try the problem without the MLE part, such that you could check the state-space representation. For example,áobtaining filtered data. Passing that test, it means that optimization is the problem. In that case,áa good startingáparameter-vector can be obtained from theáassociated ARIMA (or SARIMA) model.
á
Best, Rodrigo.

á
2012/5/29 Paolo Chirico <paolo.chirico@unito.it>
I have run the following script for local linear model with quarterly seasonality:

scalar r = 10
scalar s1=1
scalar s2=1
scalar s3=1

matrix z = {1; 0; 1; 0; 0}

matrix Q = {s1^2,ááá 0,ááá 0,ááá 0,ááá 0;ááá 0,ááá s2^2,ááá 0,ááá 0,ááá 0;ááá 0,ááá 0,ááá s3^2,ááá 0,ááá 0;ááá 0,ááá 0,ááá 0,ááá 0,ááá 0;ááá 0,ááá 0,ááá 0,ááá 0,ááá 0}

matrix T = {1,ááá 1,ááá 0,ááá 0,ááá 0;ááá 0,ááá 1,ááá 0,ááá 0,ááá 0;ááá 0,ááá 0,ááá -1,ááá -1,ááá -1;ááá 0,ááá 0,ááá 1,ááá 0,ááá 0;ááá 0,ááá 0,ááá 0,ááá 1,ááá 0}


kalman
ááá obsy y
ááá obsymat z
ááá statemat T
ááá obsvar r
ááá statevar Q
end kalman --diffuse

mle ll = ERR ? NA : $kalman_llt
ááá ERR = kfilter()
ááá params r s1 s2 s3
end mle

The model is a local linear model with quarterly seasonal.

But, I get the following error:á failed to invert OPG matrix GG'

Where is the error? In the initial values of r, s1,..., in the script, or in kfilter()?

Best regards,
Paolo
-- 
Paolo Chirico
Statistica Economica
Dipartimento di Economia
"S. Cognetti de Martiis"
UniversitÓ di Torino

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