CU Boulder News & Events

Modeling space-time variability using multivariate semi-Bayesian hierarchical framework for seasonal total and extreme precipitation in the U.S. Northern Great Plains

We adapt a semi-Bayesian hierarchical modeling framework to jointly characterize the space–time variability of seasonal precipitation totals and precipitation extremes across the Northern Great Plains ...
JSTOR Daily

A Bayesian Hierarchical Model for Prediction of Latent Health States from Multiple Data Sources with Application to Active Surveillance of Prostate Cancer

This is a preview. Log in through your library . Abstract In this article, we present a Bayesian hierarchical model for predicting a latent health state from longitudinal clinical measurements. Model ...
JSTOR Daily

Predicting spatiotemporal abundance of breeding waterfowl across Canada: A Bayesian hierarchical modelling approach

Aim: Our aim was to develop predictive statistical models for mapping the abundance of 18 waterfowl species at a pan-Canadian level. We refined the previous generation of national waterfowl models by ...
Kaleido Scope

BhGLM- Bayesian hierarchical GLMs and survival models, with applications to genomics and epidemiology

BhGLM is a freely available R package that implements Bayesian hierarchical modeling for high-dimensional clinical and genomic data. It consists of functions for setting up various Bayesian ...
CU Boulder News & Events

Bayesian Hierarchical Network Model for Forecasting Daily River Stage in a River Network

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 ...