/PyProcess

Generate stochastic processes using Python. Unfortunately not maintained any longer =(

Primary LanguagePythonOtherNOASSERTION

PyProcess 0.2

PyProcess is a Python class library used to exactly simulate stochastic processes, and their properties.

Using this library, you can simulate the following random processes:

Continuous Diffusions

  • Brownian Motion
  • Geometric Brownian Motion
  • CEV
  • CIR
  • Square Bessel Process
  • Ornstein Uhlenbeck process
  • Time-integrated Ornstein Uhlenbeck process
  • Levy Processes
  • Bessel Process (coming soon)
  • Fractional Brownian Motion (coming soon)

Jump Diffusions

  • Gamma process
  • Variance-gamma process
  • Geometric Gamma process
  • Inverse Gaussian process NEW
  • Normal Inverse Gaussian process NEW

Step Processes

  • Renewal process
  • Poisson process
  • Compound poisson process
  • marked-poisson process
  • Fractional poisson process (coming soon)

See fun examples of the processes you can simulate [here] (http://pyprocess.70percentfatfree.com)

Simulation Algorithms + PyProcess 0.2

See the report for PyProcess 0.2's background.

Lastly

Visit me at camdp.com or at @cmrn_dp