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 > > ______________________________________________ > R-help <at> stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > >
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) ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
