How to Get the Variance-Covariance Matrix after getting the estimation parameters

Dear Sir,

I would like to know how to get the matrix of variance-covariance of parameter estimates using the Maximum likelihood procedure,

I mean after getting the results of the parameters I wan also to know the Variance-Covariance matrix of these parameters, as an extra output of the model estimation.

I have tried to use the following,

y=vcm(_max_FinalHess);

but I don't think its correct!

its so necessary to conduct Andrew's test which needs (f-fe)'V(f-fe), where V: is the varaince-covaraince of the parameter estiamtes

 

Thank you very much

 

2 Answers



0



Hi,

If you are using the maximum likelihood package, you should have the following code to call the package in your estimation:

{x,f,g, vc, retcode} = maxlik(data,var,&fct,start);

which basically stores the estimated variance-covariance matrix in the global variable named `vc'.

It will also be printed to the output window by the following code:

maxprt(x,f,g,vc,retcode);

Hope this helps.

Cheers



0



Dear Sir

I would like to thank you very much for answering my question, you saved my day,

Indeed now I can recall the variance-covariance matrix as I want,

yours sincerely

Ghasak

Your Answer

2 Answers

0

Hi,

If you are using the maximum likelihood package, you should have the following code to call the package in your estimation:

{x,f,g, vc, retcode} = maxlik(data,var,&fct,start);

which basically stores the estimated variance-covariance matrix in the global variable named `vc'.

It will also be printed to the output window by the following code:

maxprt(x,f,g,vc,retcode);

Hope this helps.

Cheers

0

Dear Sir

I would like to thank you very much for answering my question, you saved my day,

Indeed now I can recall the variance-covariance matrix as I want,

yours sincerely

Ghasak


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