home/categories/scientific-computing/jkitchin-skillz-skills-scientific-design-of-experiments-skill-md
scientific-computingresearch
design-of-experiments
Expert guidance for Design of Experiments (DOE) in Python - interactive goal-driven design selection, classical DOE (factorial, response surface, screening), Bayesian optimization with Gaussian processes, model-driven optimal designs, active learning, and sequential experimentation; includes pyDOE3, pycse, BoTorch, Ax, scikit-optimize, statsmodels
maintainer
jkitchin
更新日 3/7/2026
スター
24
フォーク
5
quick start
Installation and usage
Expert guidance for Design of Experiments (DOE) in Python - interactive goal-driven design selection, classical DOE (factorial, response surface, screening), Bayesian optimization with Gaussian processes, model-driven optimal designs, active learning, and sequential experimentation; includes pyDOE3, pycse, BoTorch, Ax, scikit-optimize, statsmodels
インストール
$ install --globalskills.sh
使い方
インストール後、ターミナルで以下のコマンドを実行してこのスキルを使用できます：
skills use design-of-experiments