R: Fisher information matrix for Theta

fisher {PLNmodels} | R Documentation

## Fisher information matrix for Theta

### Description

Extracts Fisher information matrix of Θ 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(θ)

.

### Usage

    fisher(object, type)

    ## S3 method for class '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 Θ is a matrix of size d * p.

### Methods (by class)

- `PLNfit`: Fisher information matrix for PLNfit

### See Also

`standard_error` for standard errors

[Package PLNmodels version 0.11.6 Index]