R: MLE for multivariate discrete data

MLE for multivariate discrete data {Rfast} | R Documentation

## MLE for multivariate discrete data

### Description

MLE for multivariate discrete data.

### Usage

    multinom.mle(x)
    dirimultinom.mle(x, tol = 1e-07)
    colpoisson.mle(x)
    colgeom.mle(x, type = 1)

### Arguments

`x` | A matrix with discrete valued non negative data.
`tol` | the tolerance level to terminate the Newton-Raphson algorithm for the Dirichlet multinomial distribution.
`type` | This is for the geometric distribution only. Type 1 refers to the case where the minimum is zero and type 2 for the case of the minimum being 1.

### Details

For the Poisson and geometric distributions we simply fit independent Poisson and geometric distributions respectively.

### Value

A list including:

`loglik` | A vector with the value of the maximised log-likelihood.
`param` | A vector of the parameters.

### Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@uoc.gr> and Manos Papadakis <papadakm95@gmail.com>.

### References

Johnson Norman L., Kotz Samuel and Balakrishnan (1997). Discrete Multivariate Distributions. Wiley

Minka Thomas (2012). Estimating a Dirichlet distribution. Technical report.

### See Also

`poisson.mle, zip.mle, ztp.mle, negbin.mle, poisson.nb`

### Examples

    x <- t( rmultinom(1000, 20, c(0.4, 0.5, 0.1) ) )
    res<-multinom.mle(x)
    res<-colpoisson.mle(x)
    x <- NULL

[Package Rfast version 2.0.4 Index]