We present an approach for correcting for interobserver measurement error in an ordinal logistic regression model taking into account also the variability of the ...

We develop a Bayesian nonparametric framework for modeling ordinal regression relationships, which evolve in discrete time. The motivating application involves a key problem in fisheries research on ...

Some of you may have come across a growing number of publications in your field using an alternative paradigm called Bayesian statistics in which to perform their statistical analyses. The goal of ...

Caught Looking examines articles from the academic literature relevant to baseball and statistical analysis. This review looks at the inaugural article from the Journal of Sports Analytics, written by ...

A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...