francogrex mail.com> writes:
> [SNIP]
> This maximisation involves a search in five-dimensional
> parameter space {θ: α1,α2, β1, β2, P} for the vector that maximises the
> likelihood as evidenced by the first and second derivatives of the function
> being zero. The likelihood is L(θ) = Πij {P f (
Hi guys again, it seems I haven't been doing the maximum likelihood
estimation correctly. I quote below, can someone explain to me please what
does it mean that the 2nd and 3rd derivatives of the function equals zero
and how to compute that in R.
"We have our initial estimated, subjective paramet
