| 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