A collection of functions for simulation and parameter estimation of Ornstein-Uhlenbeck processes.
Clone the repository and install the package with pip install .
Or
pip install git+https://github.com/jwergieluk/ou_noise.git
The following IPython session demonstrates the package usage.
from ou_noise import ou
import numpy
import matplotlib.pyplot as plt
%matplotlib
t = numpy.arange(0, 100, 0.01)
# simulate a path of the OU process on a given grid t, starting with x_0 = 0.8
x = ou.path(0.8, t, 2.0, 0.5, 0.05)
plt.plot(t,x)
params = ou.mle(t, x)
print(params)
# Output: [2.09360033 0.49863601 0.04992896]
The plot generated by the above script:
ou_noise is released under the GNU GENERAL PUBLIC LICENSE Version 3. See LICENSE file for details.
Copyright (c) 2016--2019 Julian Wergieluk