For running psychology and neuroscience experiments

Create behavioral experiments in a browser using JavaScript

A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.

YACS -- Yet Another Configuration System

Causal Inference for The Brave and True 책의 한국어 번역 자료입니다.

A JavaScript port of Facebook's PlanOut Experimentation Framework

Bayesian Optimization and Design of Experiments

Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.

Olympus: a benchmarking framework for noisy optimization and experiment planning

This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design for designing randomized paired geo experiments.

Experimental design and (multi-objective) bayesian optimization.

Causal Inference Using Quasi-Experimental Methods

Experimental design and Bayesian optimization library in Python/PyTorch

Stochastic System Identification Toolkit (SSIT) to model, analyze and design single-cell experiments

게임 데이터를 통해 인과관계를 추론하는 능력을 향상시킬 수 있는 책입니다.

A Python Package for intuitive design of experiments with user-friendly analysis of results. The aim is for this package to rival the DOE capabilities of commercial software such as JMP. Currently designs and analysis will be more geared towards investigations following the Response Surface Methodology.

ParamHelpers Next Generation

Experimental Design & Recommendations Project of Udacity Data Scientist Nanodegree

Repository for the paper "Optimal design of stochastic DNA synthesis protocols based on generative sequence models" (Weinstein et al., AISTATS, 2022).