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I have a likelihood function in R that I am optimizing using 'optim' and calculating the hessian matrix using hessian=T in the optim function. I want to calculate the Godambe Information matrix in R, which is defined as:

G(theta)= H(theta) J(theta)^-1 H(theta)

where J(theta) is the variability matrix and H(theta) is the sensitivity matrix.

I am not sure how to calculate these matrices in R for my likelihood function and the estimates obtained from the optim. Please help.

Roopali Singh
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  • There is a function [godambe](https://www.rdocumentation.org/packages/weightedScores/versions/0.9.5.3/topics/godambe) in package `weightedScores`. – Rui Barradas Jul 03 '21 at 17:02
  • @RuiBarradas I checked that one but it seems that it is specific to certain likelihoods such as poisson, bernoulli and negative binomial. – Roopali Singh Jul 03 '21 at 19:03
  • Perhaps try asking this question on [Cross Validated](http://www.stats.stackexchange.com) - you'll have a better chance of getting a reliable answer, given the theme of your question. – Rory S Jul 04 '21 at 15:52

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