Welcome to EXperimental PLANNing Documentation’s documentation!

Python package for EXperimental PLANNing course. It implements classes to build and analise statistical (mainly focused on factorial) models.

Statisctical models are built by statsmodels.

Installation

If you have git and installed, just clone this repository

git clone https://github.com/properallan/explann```

move to the root folder

cd explann

then

pip install -e .

Documentation

The documentation is available at https://explann.readthedocs.io/en/latest/

Contents:

• explann
  • explann package
• Examples
  • Begginer’s Tutorial
  • Case Study
  • Factorial \(2^4\)
  • explann hands-on on \(2^4\) design
  • Factorial \(2^3\)
  • building a model with explann
  • Central Composite Design
  • Optimization Using Desirabilty Function
  • Anova table and lack of fit
  • Optmization Results
  • Proposal Study
  • Main Hypotesis
  • Central Composite Design
  • Dependent variables (Order Reduction)
  • Fitting Factorial Model
  • Resulting Model for principal components
  • Test Model Accuracy
  • References

Indices and tables

• Index

• Module Index

• Search Page