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When solving the log likelihood expression for autoregressive models, I cam across the variance covariance matrix Tau given under slide 9 Parameter estimation of time series tutorial. Now, in order to use 

fminsearch

to maximize the likelihood function expression, I need to express the likelihood function where the variance covariance matrix arises. Can somebody please show with an example how I can implement (determinant of Gamma)^-1/2 ? Any other example apart from autoregressive model will also do.

SKM
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How about sqrt(det(Gamma)) for the sqrt-determinant and inv(Gamma) for inverse?

But if you do not want to implement it yourself you can look at yulewalkerarestimator

UPD: For estimation of autocovariance matrix use xcov

also, this topic is a bit more explained here

Dima Lituiev
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  • Thank you for the commands which was par of my problem. My other concern was how do I form the elements of the Gamma matrix? – SKM Nov 22 '14 at 22:53