[R] R and MLE

[Ajay Narottam Shah]

I learned R & MLE in the last few days. It is great! I wrote up my
explorations as

  http://www.mayin.org/ajayshah/KB/R/mle/mle.html

I will be most happy if R gurus will look at this and comment on how
it can be improved.



I have a few specific questions:

* Should one use optim() or should one use stats4::mle()?

  I felt that mle() wasn't adding much value compared with optim, and
  in addition, I wasn't able to marry my likelihood functions to it.

* One very nice feature of mle() is that you can specify a few
  parameters which should be fixed in the estimation. How can one
  persuade optim() to behave like that?

* Can one use deriv() and friends to get analytical derivatives of
  these likelihood functions? I found I wasn't able to make headway
  when I was using vector/matrix notation. I think the greatness of R
  lies in a lovely vector/matrix notation, and it seems like a shame
  to have to not use that when trying to do deriv().

* For iid problems, the computation of the likelihood function and
  it's gradient vector are inherently parallelisable. How would one go
  about doing this within R?

-- 
Ajay Shah                                                   Consultant
ajayshah at mayin.org                      Department of Economic Affairs
http://www.mayin.org/ajayshah           Ministry of Finance, New Delhi