Generic method for computing the observed FIM of an `mle` object.

Fisher information is a way of measuring the amount of information that an observable random variable `X` carries about an unknown parameter `theta` upon which the probability of `X` depends.

Usage

observed_fim(x, ...)

Arguments

x

the object to obtain the fisher information of

...

additional arguments to pass

Details

The inverse of the Fisher information matrix is the variance-covariance of the MLE for `theta`.

Some MLE objects do not have an observed FIM, e.g., if the MLE's sampling distribution was bootstrapped.