DOI QR코드

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Hierarchical Bayes Analysis of Smoking and Lung Cancer Data

  • 발행 : 2002.04.01

초록

Hierarchical models are widely used for inference on correlated parameters as a compromise between underfitting and overfilling problems. In this paper, we take a Bayesian approach to analyzing hierarchical models and suggest a Markov chain Monte Carlo methods to get around computational difficulties in Bayesian analysis of the hierarchical models. We apply the method to a real data on smoking and lung cancer which are collected from cities in China.

키워드

참고문헌

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피인용 문헌

  1. A Space-Time Model with Application to Annual Temperature Anomalies; vol.10, pp.1, 2003, https://doi.org/10.5351/CKSS.2003.10.1.019