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 ...

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 ...

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 ...

We present a Bayesian hierarchical model for detecting differentially expressing genes that includes simultaneous estimation of array effects, and show how to use the output for choosing lists of ...

A standard tool for model selection in a Bayesian framework is the Bayes factor which compares the marginal likelihood of the data under two given different models. In this paper, we consider the ...

Peatlands regulate atmospheric greenhouse gas concentrations and thus the global climate. They form one of the largest terrestrial C stores and current and projected long-term shifts in temperature, ...

What Is A Hierarchical Models? Hierarchical models, also known as hierarchical statistical models, multilevel models or random-effects models, are tools for analysing data with a nested or grouped ...

The purpose of this trial was to assess the efficacy of imatinib in patients with one of 10 different subtypes of advanced sarcoma. Eligible patients were treated daily with imatinib dosed at 300 mg ...