59 results for “topic:doe”
Design of Experiment Generator. Read the docs at: https://doepy.readthedocs.io/en/latest/
qd python library for CAE (currently mostly LS-Dyna)
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
Space filling designs for python
Matlab tools for design of experiments and response surface
Optimization framework library fully written in C++
No description provided.
Formula parser and evaluator for Wilkinson Notation and dataframes arithmetics
Design, analyze, and optimize screening experiments with DoE, statistics, and Bayesian Optimization
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).
No description provided.
This is a story about statistics, experiments and tests.
A/B Testing from Scratch
Shiny app for our catalog of four-and-two-level designs
Repository for work performed for NYCC 9/22 Technology Oversight Hearing on the Digital Divide
Projeto desenvolvido na semana NLW
This code will run the analysis for a 2k Factorial design of experiments test with 1 to 26 variable parameters of interest.
Applied statistical analysis and data modeling in R, focused on Quality Engineering, Design of Experiments (DoE), and process optimization across industrial and business sectors.
Generate and characterize designs with four-and-two-level (FATL) factors.
Examine student health reports to gain insights into the locations of SBHCs
📊 STAT 454/545: Analysis of Variance and Experimental Design.
The Official Best Way to Prepare for Science Bowl (SciBowl) MS & HS
Easy DOE
This package provides the tools to enumerate and characterize regular mixed-level designs (with four and two-level factors).