[R] maximum likelihood standard deviation

[Ben Bolker]

Carlo Fezzi <fezzi <at> stat.unibo.it> writes:

> 
> Dear R-helpers,
> Anybody knows which function can I use to comupute maximum likelihood
> standard errors?
> 
> Using the function "nlm" I can get the estimate of the parameters of any
> likelihood that I want (for example now I am working on a jump diffusion
> process) but what about the standard error?
> 
> Is there a function that I can use to calculate the second derivate of
> the likelihood function respect to the vector of parameters?
> 
> Thank you so much for your help,
> 
> Carlo Fezzi
> 
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> 


  if you set hessian=TRUE when calling nlm it will give you
exactly what you want -- second derivative [sic] of the
likelihood w.r.t. parameters (provided of course that your
objective function in nlm() is the negative log-likelihood).
solve() on the hessian should invert the Hessian and give
you the variance-covariance matrix (then sqrt(diag()) to
get the s.d.s)