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 ...

Bayesian hierarchical modeling is a popular approach to capturing unobserved heterogeneity across individual units. However, standard estimation methods such as Markov chain Monte Carlo (MCMC) can be ...

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 spatial Bayesian hierarchical model for seasonal extreme precipitation. At the first level of hierarchy, the seasonal maximum precipitation (i.e. block maxima) at any location is assumed ...

A research team introduces a hierarchical Bayesian spatial approach that integrates UAV and terrestrial LiDAR data to estimate AGB of individual trees in natural secondary forests of northeastern ...

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 ...