Kalman Filter: Asymmetric covariance matrix

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pcruzd
Posts: 15
Joined: Thu Dec 14, 2017 11:53 am

Kalman Filter: Asymmetric covariance matrix

Postby pcruzd » Mon Jul 29, 2019 10:46 am

Hi I am estimating a State Space model that has two state variables x and y, with errors res_x and res_y. res_x variance is not affected by res_y, but the variance of res_y is affected by res_x. However, i am not sure how to estimate such a structure in Eviews. What I am looking is to specify the model such as:

Code: Select all

@ename res_x @ename res_y @evar var(res_x) = exp(c(1)) @evar var(res_y) = exp(c(2)) @evar cov(res_x, res_y) = 0 @evar cov(res_y, res_x) = c(3)
I know the latter is wrong as the cov(x,y) command is symmetric, so I need to know if there is any way to compute such assymetric covariance matrix.

startz
Non-normality and collinearity are NOT problems!
Posts: 3797
Joined: Wed Sep 17, 2008 2:25 pm

Re: Kalman Filter: Asymmetric covariance matrix

Postby startz » Mon Jul 29, 2019 11:01 am

By definition, a covariance is symmetric. Nothing to do with EViews.

Sounds like you may want to build a model of the errors explicitly into the state space model.

pcruzd
Posts: 15
Joined: Thu Dec 14, 2017 11:53 am

Re: Kalman Filter: Asymmetric covariance matrix

Postby pcruzd » Mon Jul 29, 2019 12:02 pm

you are right, already modelled the errors explicitly. Thanks!


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