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خانوادهProcess / pipelineProcess / pipeline
سال پیدایش1990s (Bayesian DOE formalized); factorial design roots in 1920s (Fisher)1956 (foundational); formalized 1970s–1990s
پدیدآورKathryn Chaloner & Isabella Verdinelli (Bayesian experimental design framework); building on Fisher's factorial design principlesLindley (1956); Chaloner & Verdinelli (1995) landmark review
نوعBayesian experimental design methodBayesian optimal experimental design
منبع بنیادینChaloner, K., & Verdinelli, I. (1995). Bayesian experimental design: A review. Statistical Science, 10(3), 273–304. DOI ↗Chaloner, K., & Verdinelli, I. (1995). Bayesian Experimental Design: A Review. Statistical Science, 10(3), 273–304. DOI ↗
نام‌های دیگرBayesian FFD, Bayesian complete factorial experiment, Bayesian full factorial experiment, Bayesian all-combinations designBayesian DOE, Bayesian optimal design, Bayesian experimental design, BDE
مرتبط33
خلاصهBayesian full factorial design combines the complete combinatorial structure of classical full factorial experiments — running every combination of factor levels — with a Bayesian inferential framework that incorporates prior knowledge about factor effects and yields full posterior distributions over main effects, interactions, and model parameters, rather than point estimates and p-values.Bayesian design of experiments selects experimental runs by maximising a utility function — typically the expected information gain — computed over prior beliefs about model parameters. Unlike classical design, which optimizes algebraic criteria such as D-optimality under fixed assumptions, Bayesian DOE incorporates prior knowledge and uncertainty about the system, yielding designs that are optimal in expectation across all plausible parameter values.
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ScholarGateمقایسهٔ روش‌ها: Bayesian Full Factorial Design · Bayesian Design of Experiments. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare