MLE of the inverted Dirichlet distribution
MLE of the inverted Dirichlet distribution.
invdir.mle(x, tol = 1e-09)
x |
A matrix with strictly positive data (no zeros are allowed). |
tol |
The tolerance level up to which the maximisation stops. |
Maximum likelihood estimation of the parameters of the inverted is performed via Newton-Raphson. We took the initial values suggested by Bdiri T. and Bouguila N. (2012) and modified them a bit.
A list including:
iters |
The number of iterations required by the Newton Raphson. |
loglik |
The value of the log-likelihood. |
param |
The estimated parameters. |
Michail Tsagris
R implementation and documentation: Michail Tsagris <mtsagris@yahoo.gr> and Manos Papadakis <papadakm95@gmail.com>
Bdiri T. and Bouguila N. (2012). Positive vectors clustering using inverted Dirichlet finite mixture models. Expert Systems with Applications, 39(2): 1869-1882.
x <- as.matrix(iris[, 1:4]) system.time( for(i in 1:100) invdir.mle(x) ) res<-invdir.mle(x)
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