Scoring rules assess the quality of probabilistic forecasts, by assigning a numerical score
based on the predictive distribution and on the event or value that materializes. A scoring …

When analyzing time-to-event data, it often happens that a certain fraction of the data
corresponds to subjects who will never experience the event of interest. These event times …

The method of model averaging has become an important tool to deal with model
uncertainty, for example in situations where a large amount of different theories exist, as are …

The steady upward trend in the use of model selection and Bayesian methods in ecological
research has made it clear that both approaches to inference are important for modern …

Spatial process models for analyzing geostatistical data entail computations that become
prohibitive as the number of spatial locations become large. This article develops a class of …

Bayesian modeling has become an indispensable tool for ecological research because it is
uniquely suited to deal with complexity in a statistically coherent way. This textbook provides …

The goal of this paper is to compare several widely used Bayesian model selection methods
in practical model selection problems, highlight their differences and give recommendations …

We consider the problem of comparing complex hierarchical models in which the number of
parameters is not clearly defined. Using an information theoretic argument we derive a …

Abstract Model building and data analysis in the biological sciences somewhat presupposes
that the person has some advanced education in the quantitative sciences, and statistics in …

Bayesian Data Analysis describes how to conceptualize, perform, and critique statistical
analyses from a Bayesian perspective. Using examples largely from the authors' own …