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ベイズ型ゼロ過剰モデル×ベイズ一般化線形モデル×
分野統計学統計学
系統Regression modelRegression model
提唱年1992–20061989 (GLM); 1995 (Bayesian BDA)
提唱者Lambert (1992) for ZIP; Bayesian extension by Ghosh, Mukhopadhyay & Lu (2006)McCullagh & Nelder (GLM framework); Bayesian treatment formalized by Gelman et al.
種類Bayesian count regressionBayesian regression model
原典Ghosh, S. K., Mukhopadhyay, P., & Lu, J.-C. (2006). Bayesian analysis of zero-inflated regression models. Journal of Statistical Planning and Inference, 136(4), 1360–1375. DOI ↗Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955
別名Bayesian ZIP, Bayesian ZINB, Bayesian zero-inflated Poisson, Bayesian zero-inflated negative binomialBayesian GLM, Bayesian GLIM, Bayesian generalized linear regression, Bayes GLM
関連56
概要The Bayesian zero-inflated model handles count data with excess zeros by combining a binary component — identifying structural zeros — with a count component (Poisson or negative binomial) for the remaining counts. Bayesian inference via MCMC provides full posterior distributions for all parameters, enabling principled uncertainty quantification and regularisation through priors.A Bayesian Generalized Linear Model (Bayesian GLM) extends the classical GLM framework by placing prior distributions on the regression coefficients and updating them with data via Bayes' theorem. This yields a full posterior distribution over parameters rather than single point estimates, enabling richer uncertainty quantification and principled incorporation of prior knowledge for any exponential-family outcome.
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ScholarGate手法を比較: Bayesian Zero-inflated model · Bayesian Generalized Linear Model. 2026-06-15に以下より取得 https://scholargate.app/ja/compare