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बेयसियन ज़ीरो-इन्फ्लेटेड मॉडल×शून्य-स्फेतित मॉडल (Zero-Inflated Model)×
क्षेत्रसांख्यिकीसांख्यिकी
परिवारRegression modelRegression model
उद्भव वर्ष1992–20061992
प्रवर्तकLambert (1992) for ZIP; Bayesian extension by Ghosh, Mukhopadhyay & Lu (2006)Diane Lambert
प्रकारBayesian count regressionCount regression with excess zeros
मौलिक स्रोतGhosh, 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 ↗Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1–14. DOI ↗
उपनामBayesian ZIP, Bayesian ZINB, Bayesian zero-inflated Poisson, Bayesian zero-inflated negative binomialZIP model, ZINB model, zero-inflated Poisson, zero-inflated negative binomial
संबंधित56
सारांशThe 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 zero-inflated model is a two-component mixture regression designed for count outcomes that contain more zero values than a standard Poisson or negative binomial distribution can accommodate. One component is a binary process that generates structural zeros; the other is a count process that generates both zeros and positive counts.
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