https://github.com/abdulfatir/sampling-methods-numpy

This repository contains implementations of some basic sampling methods in numpy.
https://github.com/abdulfatir/sampling-methods-numpy

ipython-notebook metropolis-hastings monte-carlo monte-carlo-methods numpy python

Last synced: about 1 month ago
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This repository contains implementations of some basic sampling methods in numpy.

• Host: GitHub
• URL: https://github.com/abdulfatir/sampling-methods-numpy
• Owner: abdulfatir
• Created: 2018-03-03T18:13:39.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-03-28T15:06:59.000Z (over 4 years ago)
• Last Synced: 2024-09-28T23:23:44.921Z (about 2 months ago)
• Topics: ipython-notebook, metropolis-hastings, monte-carlo, monte-carlo-methods, numpy, python
• Language: Jupyter Notebook
• Homepage:
• Size: 517 KB
• Stars: 63
• Watchers: 6
• Forks: 14
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Sampling Methods in Numpy

This repository contains code for some basic sampling methods implemented using numpy.    

The following methods are implemented with examples

* Importance Sampling (Univariate example)

* Rejection Sampling (Univariate example)

* Metropolis-Hastings (Univariate and Multivariate example)

* Gibbs Sampling (Multivariate example)

* Langevin Monte Carlo

  * Unadjusted Langevin Algorithm (ULA) - Pytorch

  * Metropolis-adjusted Langevin Algorithm (MALA) - Pytorch

* Inverse Transform Sampling

  * Cauchy Distribution

  * Exponential Distribution

  * Gumbel Distribution