Estimating a parameter vector of a maximum likelihood function

Dead Community,

I am an undergraduate economics student and I am facing following problem.

I want to estimate a parameter vector which contains alpha, epsilon, mu and delta. I got data about the variables B, S and T. The parameters are supposed to maximize the likelihood function of the formula in the picture. Could anybody please give me a hint how to code this problem? So far I only coded OLS estimations...

Best regards

Answer 1

[Jeff Miller]

One way to proceed is to write a function which accepts a set of values for alpha, epsilon, mu, and delta, and returns -log(L) under those parameter values. Then you use fminsearch to minimize that function. fminsearch will try different values of the parameter values and do the best it can to minimize -log(L), which maximizes L. There are no guarantees of finding the best parameter values this way, but it is a common approach when it is too hard to maximize L mathematically.

[Hasan Yagmur]

Thank you @Jeff Miller