Design of Experiment Generator. Read the docs at: https://doepy.readthedocs.io/en/latest/
FielDHub is an R Shiny design of experiments (DOE) app that aids in the creation of traditional, unreplicated, augmented and partially replicated (p-rep) designs applied to agriculture, plant breeding, forestry, animal and biological sciences.
Curated list of resources for the Design of Experiments (DOE)
A python package for optimizing processing pipelines using statistical design of experiments (DoE).
R package of comprehensive tools for designing and analyzing choice-based conjoint (cbc) experiments
Design of Experiments and Analysis
This MultiDOE toolbox regroups many existing tools for generating sample points using many specific DOE techniques.
ChemDesign: DWSIM Experiment Toolkit
Process Analytics & Six Sigma in Python — integrated workflows for capability analysis, root cause analysis, and statistical process control.
Optimization framework library fully written in C++
Formula parser and evaluator for Wilkinson Notation and dataframes arithmetics
Design, analyze, and optimize screening experiments with DoE, statistics, and Bayesian Optimization
This is a story about statistics, experiments and tests.
8 hands-on Certified Lean Six Sigma Black Belt labs covering DMAIC, project charter, VOC, SIPOC, MSA, capability, hypothesis testing, regression, DOE, FMEA, SPC, control plans, benefits realization, and exam review.
Universal framework for LLM Prompt Optimization using Fractional Factorial Design of Experiments (DoE) & ANOVA
MATLAB app that can plot the design space and results of a experiment in up to five dimensions (x, y, z, colour and dot size).
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