方法证据记录
Bayesian Fractional Factorial Design
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Bayesian Fractional Factorial Experimental Design
分类方法记录 · process-pipeline / experimental-design
- 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 10.2307/1269197
- Meyer, R. D., & Steinberg, D. M. (1996). Follow-up designs to resolve confounding in multifactor experiments. Technometrics, 38(4), 303–313. · DOI 10.1080/00401706.1996.10484538
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