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
Universal framework for LLM Prompt Optimization using Fractional Factorial Design of Experiments (DoE) & ANOVA
Design, analyze, and optimize screening experiments with DoE, statistics, and Bayesian Optimization
This is a story about statistics, experiments and tests.
WSQ Certified Lean Six Sigma Black Belt (CLSSBB) Training, TGS-2024051900. 5-day practitioner course with 34 hands-on activity packs and a capstone improvement project, plus the full slide deck, Learner Guide and Lesson Plan.
Janus Architecture post-transformer inference in Arianna Method Language
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