The development of methods for dealing with continuous data with a spike at zero has
lagged behind those for overdispersed or zero‐inflated count data. We consider longitudinal …

Coral reefs have become one of the most vulnerable ecosystems worldwide due to rising
environmental and anthropogenic pressures. Methods from experimental design can be …

This introductory chapter is about fundamental ideas involved in model selection such as
between a model-based or design-based approach, or a combination of both, and between …

This article shows reparameterization technique that is used to improve the mixing of Markov
Chain Monte Carlo (MCMC) algorithms. Moreover, one of the main reasons for MCMC …

The theory of sampling has been well described in the literature, but with less emphasis on
density estimation. The topics covered are simple random sampling and associated design …

Abstract Reversible jump Markov chain Monte Carlo (RJMCMC) is a Bayesian model
estimation method, which has been generally used for trans-dimensional sampling and …

The main objective of this thesis is to suggest a general Bayesian framework for model
selection based on reversible jump Markov chain Monte Carlo (RJMCMC) algorithm. In …

Bayesian inference and rare event simulation increase in complexity when model
parameters are represented through random fields. We propose two algorithms that are …

Coral reefs have become one of the most vulnerable ecosystems worldwide due to rising
environmental and anthropogenic pressures. Methods from experimental design can be …

Severe declines in the number of some songbirds over the last 40 years have caused
heated debate amongst interested parties. Many factors have been suggested as possible …