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 ...
https://doi.org/10.1525/auk.2009.09015 • https://www.jstor.org/stable/10.1525/auk.2009.09015 Copy URL Abstract Models for estimating survival probability of nests ...
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 ...
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 ...
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 ...
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 ...
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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback