sampling from univariate distributions
Project description
samplepy implements three sampling methods for univariate distributions. The package includes:
- Importance sampling: samplepy.Importance
- Rejection sampling: samplepy.Rejection
- Metropolis-Hastings sampling: samplepy.MH
Examples:
from samplepy import Rejection import matplotlib.pyplot as plt import numpy as np """ Rejection sampling example from 2 different functions """ # define a unimodal function to sample under f = lambda x: 2.0*np.exp(-2.0*x) rej = Rejection(f, [0.01, 3.0]) # instantiate Rejection sampling with f and interval sample = rej.sample(10000, 1) # create a sample of 10K points x = np.arange(0.01, 3.0, (3.0-0.01)/10000) fx = f(x) figure, axis = plt.subplots() axis.hist(sample, normed=1, bins=40) axis2 = axis.twinx() axis2.plot(x, fx, 'g', label="f(x)=2.0*exp(-2*x)") plt.legend(loc=1) plt.show()
More examples and package documentation can be found at <https://github.com/elena-sharova/samplepy/blob/master/README.rst>
Installation
pip install samplepy
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