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Fitting More Complex Bayesian Models: Markov Chain Monte Carlo,ly. In more realistic and complex Bayesian models, such analytical calculations generally are not feasible. This chapter introduces the sampling-based methods of fitting Bayesian models that have transformed Bayesian statistics over the last 20 years.冷漠 发表于 2025-3-27 08:58:33
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Model Comparison, Model Checking, and Hypothesis Testing,riteria for determining which of the candidate models is best, and whether even that model is good enough to use as the basis for inference. This chapter considers Bayesian methods of comparing models, testing hypotheses, and assessing model adequacy.ingrate 发表于 2025-3-27 20:35:15
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Mary Kathryn CowlesPractical approach is good for students of all levels.Based on over 12 years teaching Bayesian Statistics.R and OpenBUGS are essential to modern Bayesian applicationsCONE 发表于 2025-3-28 08:33:42
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Textbook 2013hods, specifying hierarchical models, and assessing Markov chain Monte Carlo output. . .Kate Cowles taught Suzuki piano for many years before going to graduate school in Biostatistics. Her research areas are Bayesian and computational statistics, with application to environmental science. She is o