Bayesian hierarchical modeling

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

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.

2016

2016

Bayesian analysis is a flexible statistical methodology for inferring properties of unknown parameters by combining observational…

2015

Common statistical practice has shown that the full power of Bayesian methods is not realized until hierarchical priors are used…

2013

Fully Bayesian estimat ion has been developed for unidimensional IRT models. In this context, prior distributions can be…

2010

Many marine species exhibit temporal variation in individual growth. Yearly variation in growth has been identified for red…

2009

Adverse weather has a major safety impact on travelers on highways. Weather events and their impact on highways can be viewed as…

2008

Analysis of spatial panel data is of great importance and inter- est in spatial econometrics. Here we consider cigarette demand…

2006

Bayesian methods offer an attractive framework for the analysis of PKPD experiments. Previous limitations associated with…

2004

There are many challenges with assessing the reliability of a system today. These challenges arise because a system may be aging…

Review

2003

Review

2003

In this paper, Bayesian hierarchical modeling techniques are used to identify and rank hazardous intersections for bicycles in…