Space-filling Design of Experiments for Python: optimal sampling for discrete, continuous, integer and mixed parameter spaces
Framework for design and evaluation of Bandit algorithms with underlying Bayesian models
EDI (Experimental Design and Inference): R & Python packages for fixed and sequential randomized experimental designs (blocking, optimal, matching-on-the-fly) with matched exact, asymptotic, and randomization inference for continuous, count, proportion, survival, and ordinal responses. C++ core. Not Electronic Data Interchange.
A small collection of python-scripts associated with Gaussian process emulators in Bayesian inverse problems
POSSA: Power simulation for sequential analyses and multiple hypotheses.
GPmp extensions
Code and frozen artifacts for replicated-bank dual-objective repair in learned sequential experimental design
To associate your repository with the sequential-design topic, visit your repo's landing page and select "manage topics."