EM algorithms for fitting multistate cure models

Fitting Mixed-Effects Models Using Efficient EM-Type Algorithms

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Fitting Algorithms for MMPP ATM Traffic Models

In this paper, we propose and study fitting algorithms for MMPP(2) and CMPP ATM traffic models, which are special cases of Markov Modulated Poisson Processes (MMPP). Two fitting algorithms, both based on the cell interarrival times, are considered for the MMPP(2) model: one fits the cumulative distribution and auto-covariance functions and other fits the first three moments and auto-covariance ...

MCMC algorithms for fitting Bayesian models

Two algorithms for fitting constrained marginal models

The two main algorithms that have been considered for fitting constrained marginal models to discrete data, one based on Lagrange multipliers and the other on a regression model, are studied in detail. It is shown that the updates produced by the two methods are identical, but that the Lagrangian method is more efficient in the case of identically distributed observations. A generalization is g...

Propagation Models and Fitting Them for the Boolean Random Sets

In order to study the relationship between random Boolean sets and some explanatory variables, this paper introduces a Propagation model. This model can be applied when corresponding Poisson process of the Boolean model is related to explanatory variables and the random grains are not affected by these variables. An approximation for the likelihood is used to find pseudo-maximum likelihood esti...