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 ...

A Bayesian hierarchical model was developed to estimate the parameters in a physiologically based pharmacokinetic (PBPK) model for chloroform using prior information and biomarker data from different ...

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 ...

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 ...

This is a preview. Log in through your library . Abstract Mortality forecasts are typically limited in that they pertain only to national death rates, predict only all-cause mortality or do not ...

Here’s our estimate of public support for vouchers, broken down by religion/ethnicity, income, and state: (Click on image to see larger version.) We’re mapping estimates from a hierarchical Bayes ...

and propagation of the leading modes of the equatorial β-plane are used. At smaller scales, once again, we invoke a wavelet decomposition constrained by the power-law behavior for wavenumber spectra ...

This study compares two different techniques in a time series small area application: state space models estimated with the Kalman filter with a frequentist approach to hyperparameter estimation, and ...