MLE for multivariate discrete data
MLE for multivariate discrete data.
multinom.mle(x) dirimultinom.mle(x, tol = 1e-07) colpoisson.mle(x) colgeom.mle(x, type = 1)
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. |
For the Poisson and geometric distributions we simply fit independent Poisson and geometric distributions respectively.
A list including:
loglik |
A vector with the value of the maximised log-likelihood. |
param |
A vector of the parameters. |
Michail Tsagris
R implementation and documentation: Michail Tsagris <mtsagris@yahoo.gr> and Manos Papadakis <papadakm95@gmail.com>.
Johnson Norman L., Kotz Samuel and Balakrishnan (1997). Discrete Multivariate Distributions. Wiley
Minka Thomas (2012). Estimating a Dirichlet distribution. Technical report.
x <- t( rmultinom(1000, 20, c(0.4, 0.5, 0.1) ) ) res<-multinom.mle(x) res<-colpoisson.mle(x) x <- NULL
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