Applied Bayesian hierarchical methods

Hierarchical Bayesian Methods in Ecology

Ecosystems are dynamic in both space and time, hence involve multiple spatial and temporal scales, and are often heterogeneous in both of those dimensions, leading to spatial and temporal clustering. Accommodating this complexity in the context of scientific (statistical) hypothesis testing necessitates more advanced methods than those available within the classical null hypothesis testing para...

Bayesian Methods for Hierarchical Distance Sampling Models

The few distance sampling studies that use Bayesian methods typically consider only line transect sampling with a half-normal detection function. We present a Bayesian approach to analyse distance sampling data applicable to line and point transects, exact and interval distance data and any detection function possibly including covariates affecting detection probabilities. We use an integrated ...

Discussion: Bayesian Methods: Applied? Yes. Philosophical Defense? In Flux

mistake that the probabilities for any binary trial are 0.5. Would anyone expect that in a random sample of two individuals from California that one would be infected with HIV and the other would not? Or expect that the sun would rise one day and not the next? In addition, uniform priors on the real line, or even normal distributions with mean zero and huge variances, say very silly things, for...

Alternative Methods for Fitting Two-Stage Hierarchical Bayesian Models

Although it is common practice to fit a complex Bayesian model using Markov chain Monte Carlo (MCMC) methods, we provide an alternative sampling-based method to fit a two-stage hierarchical model in which there is conjugacy conditional on the parameters in the second stage. Using the sampling/importance resampling (SIR) algorithm, our method subsamples independent samples from an approximate jo...

Bayesian Hierarchical Models 1 Running head: BAYESIAN HIERARCHICAL MODELS Bayesian Hierarchical Models