Welcome to JMCtools!

Python tools for perfoming Monte-Carlo studies of joint distribution functions that are built piecemeal from scipy.stats distribution objects (or any objects that ‘quack’ like them).

Contents:

• Installation
• Quick start
  • Combine independent distribution functions into a joint distribution
  • Sample from the joint distribution
  • Build relationships between model parameters and distribution parameters
  • Find maximum likelihood estimators
  • Construct test statistics
  • Limitations
• Examples from quick start
• JMCtools package
  • Submodules
  • JMCtools.common module
  • JMCtools.distributions module
  • JMCtools.models module
  • Module contents

These tools are fairly simple wrappers of scipy.stats objects, made for convenience rather than speed. Effort has been taken to make them pretty efficient, but if you use them to construct and analyse monstrously large joint PDFs then things will not be fast. For such intense usage you will need a more specialised (and more complicated!) toolkit, such as ROOT.

Indices and tables

• Index
• Module Index
• Search Page