Research focused on the isotopic composition of CO2 exchange between terrestrial ecosystems and the atmosphere has been historically constrained by the need for personnel to be present at remote field sites for sample collection. In practice, this has limited sampling frequency and duration, and potentially even biases sampling events to fair weather periods. We have developed an automated samp...

The Gibbs sampler, Metropolis’ algorithm, and similar iterative simulation methods are related to rejection sampling and importance sampling, two methods which have been traditionally thought of as non-iterative. We explore connections between importance sampling, iterative simulation, and importance-weighted resampling (SIR), and present new algorithms that combine aspects of importance sampli...

A hierarchical Bayesian model is investigated. This model can accommodate study heterogeneity in metaanalyses. The joint posterior distribution is derived by multiplying the likelihood and priors on this model. The conditional posterior distribution of all parameters is obtained for Gibbs sampler algorithm. A simulation study is then performed to demonstrate the validity of the Gibbs sampler in...

The goal of this article is an exact Bayesian analysis of the Heston (1993) stochastic volatility model. We carefully study the affect different parameterizations of the latent volatility process and the parameters of the volatility process have on the convergence and the mixing behavior of the sampler. We apply the sampler to simulated data and to some DM/US$ exchange rate data.

The gene genealogy is a tree describing the ancestral relationships among genes sampled from unrelated individuals. Knowledge of the tree is useful for inference of population-genetic parameters such as the mutation or recombination rate. It also has potential application in genomic mapping, as individuals with similar trait values will tend to be more closely related genetically at the locatio...