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Hierarchical Bayesian small area estimation for circular data
Author(s) -
HernandezStumpfhauser Daniel,
Breidt F. Jay,
Opsomer Jean D.
Publication year - 2016
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.1002/cjs.11303
Subject(s) - small area estimation , bayesian probability , estimation , bayes estimator , bayesian hierarchical modeling , computer science , statistics , mathematics , bayesian inference , engineering , systems engineering , estimator
We consider small area estimation for the departure times of recreational anglers along the Atlantic and Gulf coasts of the United States. A Bayesian area‐level Fay–Herriot model is considered to obtain estimates of the departure time distribution functions. The departure distribution functions are modelled as circular distributions plus area‐specific errors. The circular distributions are modelled as projected normal, and a regression model is specified to borrow information across domains. Estimation is conducted through the use of a Hamiltonian Monte Carlo sampler and a projective approach onto the probability simplex. The Canadian Journal of Statistics 44: 416–430; 2016 © 2016 Statistical Society of Canada