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Bayesian hierarchical modeling

Bayesian hierarchical modelling is a statistical model written in multiple levels (hierarchical form) that estimates the parameters of the posterior… 
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Related topics

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Spatial analysisStatistical model

Papers overview

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Highly Cited
2020
Highly Cited
2020
Searching for the Reference Point
Although reference dependence plays a central role in explaining behavior, little is known about the way that reference points… 
2019
2019
Pain Detection with fNIRS-Measured Brain Signals: A Personalized Machine Learning Approach Using the Wavelet Transform and Bayesian Hierarchical Modeling with Dirichlet Process Priors
Currently self-report pain ratings are the gold standard in clinical pain assessment. However, the development of objective… 
2017
2017
Bayesian Hierarchical Modeling Monthly Crash Counts on Freeway Segments with Temporal Correlation
As the basis of traffic safety management, crash prediction models have long been a prominent focus in the field of freeway… 
2016
2016
Guiding fish consumption advisories for Lake Ontario: A Bayesian hierarchical approach
2015
2015
Hierarchical Models for Causal Effects
Hierarchical models play three important roles in modeling causal effects: (i) accounting for data collection, such as in… 
2015
2015
Spatial Bayesian hierarchical modeling of precipitation extremes over a large domain
We propose a Bayesian hierarchical model for spatial extremes on a large domain. In the data layer a Gaussian elliptical copula… 
Highly Cited
2013
Highly Cited
2013
Bayesian hierarchical modeling of extreme hourly precipitation in Norway
Spatial maps of extreme precipitation are a critical component of flood estimation in hydrological modeling, as well as in the… 
2012
2012
Nonlinear Laplacian spectral analysis: capturing intermittent and low‐frequency spatiotemporal patterns in high‐dimensional data
We present a technique for spatiotemporal data analysis called nonlinear Laplacian spectral analysis (NLSA), which generalizes… 
Highly Cited
2010
Highly Cited
2010
Physics-driven Bayesian hierarchical modeling of the nanowire growth process at each scale
Despite significant advances in nanoscience, current physical models are unable to predict nanomanufacturing processes under… 
2010
2010
Incorporating temporal variation in the growth of red abalone (Haliotis rufescens) using hierarchical Bayesian growth models
Many marine species exhibit temporal variation in individual growth. Yearly variation in growth has been identified for red… 
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