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Pilna faktorālā eksperimentu plānojuma Bayesian versija×Baijesa daļējā faktoriālā plānošana×
NozareEksperimentu plānošanaEksperimentu plānošana
SaimeProcess / pipelineProcess / pipeline
Izcelsmes gads1990s (Bayesian DOE formalized); factorial design roots in 1920s (Fisher)1990s
AutorsKathryn Chaloner & Isabella Verdinelli (Bayesian experimental design framework); building on Fisher's factorial design principlesDuMouchel & Jones; Chipman, Hamada & Wu
TipsBayesian experimental design methodBayesian experimental design method
PirmavotsChaloner, K., & Verdinelli, I. (1995). Bayesian experimental design: A review. Statistical Science, 10(3), 273–304. DOI ↗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 ↗
Citi nosaukumiBayesian FFD, Bayesian complete factorial experiment, Bayesian full factorial experiment, Bayesian all-combinations designBayesian FFD, Bayesian screening design, Bayesian factor-screening experiment, BFF design
Saistītās33
KopsavilkumsBayesian 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 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.
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ScholarGateSalīdzināt metodes: Bayesian Full Factorial Design · Bayesian Fractional Factorial Design. Izgūts 2026-06-19 no https://scholargate.app/lv/compare