Extracts Fisher information matrix of $$\Theta$$ from objects returned by PLN and its variants. Fisher matrix is computed using one of two approximation scheme: wald (default, conservative, gives large confidence interval) or louis (anticonservative). Note that the Fisher information matrix is the full-data version (scaled by the number of observations), usually noted $$I_n(\theta)$$.

fisher(object, type)

# S3 method for PLNfit
fisher(object, type = c("wald", "louis"))

## Arguments

object

an R6 object with class PLNfit

type

Either wald (default) or louis. Approximation scheme used to compute the Fisher information matrix

## Value

A block-diagonal matrix with p (number of species) blocks of size d (number of covariates), assuming $$\Theta$$ is a matrix of size d * p.

## Methods (by class)

• fisher(PLNfit): Fisher information matrix for PLNfit

## See also

standard_error for standard errors