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系統Process / pipelineProcess / pipeline
提唱年1990s1956 (foundational); formalized 1970s–1990s
提唱者DuMouchel & Jones; Chipman, Hamada & WuLindley (1956); Chaloner & Verdinelli (1995) landmark review
種類Bayesian experimental design methodBayesian optimal experimental design
原典DuMouchel, W., & Jones, B. (1994). A simple Bayesian modification of D-optimal designs to reduce dependence on an assumed model. Technometrics, 36(1), 37–47. DOI ↗Chaloner, K., & Verdinelli, I. (1995). Bayesian Experimental Design: A Review. Statistical Science, 10(3), 273–304. DOI ↗
別名Bayesian FFD, Bayesian screening design, Bayesian factor-screening experiment, BFF designBayesian DOE, Bayesian optimal design, Bayesian experimental design, BDE
関連33
概要Bayesian fractional factorial design integrates Bayesian prior information into the selection and analysis of fractional factorial experiments. Rather than running every combination of factor levels, only a carefully chosen subset of runs is executed, with Bayesian inference used to estimate effects and quantify uncertainty — even when the classical aliasing structure leaves effects confounded.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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ScholarGate手法を比較: Bayesian Fractional Factorial Design · Bayesian Design of Experiments. 2026-06-19に以下より取得 https://scholargate.app/ja/compare