Welcome to POEM’s documentation!

Contents:

• Introduction
  • What is POEM
  • Capabilities
• Installation
  • How to install?
    • Installation
    • Clone
    • Test
• Quick Start
  • Input Structure
    • Simulation block
    • GlobalSettings block
    • RunInfo block
    • Files block
    • Distributions block
    • Models block
    • Functions block
    • LikelihoodModel block for Model Calibration
• Monte Carlo Sampling
• Latin Hypercube Sampling
• Train ROM
  • Train Gaussian Process Model
  • Train Dynamic Gaussian Process Model
  • Train Gaussian Polynomial Chaos Model with Sparse Grid
  • Train Dynamic Gaussian Polynomial Chaos Model with Sparse Grid
• Generate Sparse Grid Locations
  • Static Model
  • Dynamic Model
• Sensitivity Analysis
  • Static Sensitivity Analysis
  • Dynamic Sensitivity Analysis
• Bayesian Optimization
  • Example
  • Python External Model and Constrain
• Model Calibration
• Support
  • Developer:
  • Copyright:

Indices and tables

• Index

• Module Index

• Search Page

Contributions

All contributions are welcome. You can help this project grow in multiple ways, from creating an issue, reporting an improvement or a bug, and creating a pull request to the development branch. The people involved at some point in the development of the package can be found in the contributors page.