MCMC

July 12, 2022

Importance-sampling-tldr

MCMC
Importance Sampling

A short introction to Importance Sampling.
June 17, 2022

Box-Muller-tldr

MCMC
Box-Muller

A short introction to Box-Muller to generate two independent random normals.
June 13, 2022

tl;dr Detailed Balance

MCMC
Detailed Balance
Gibbs
Metropolis
Metropolis-Hastings

Detailed balance description and proof for Gibbs and Metropolis-Hastings .
June 12, 2022

tl;dr Chebychev Inequality

MCMC
Chebychev

Chebychev Inequality proof and use.
June 11, 2022

tl;dr Inverse CDF

MCMC
Inverse CDF

Monte Carlo using the Inverse CDF.
June 4, 2022

tl;dr Accept-Reject

MCMC
Accept-Reject
Weighted Bootstrap
ideas

Accept-Reject and Weighted Boostrap algorithms.
June 4, 2022

Accept-Reject-digression-tldr

MCMC
Accept-Reject

Accept-Reject intuitive description.
June 1, 2022

tl;dr Monte Carlo

MCMC

Basic Monte-Carlo description and theory.

Categories

More articles »

MCMC

A place for my collection of Monte Carlo learning and musings.

Robert Settlage https://rsettlage.github.io/

Computer simulations have always been my thing. I love Chao Theory, Fractals, and the like from a computer simulation perspective. I could code some sort of random walk up and just visualize it’s progression ad naseum. This collection is specific to my learning about and exploring Monte Carlo methods.

The two topics in Monte Carlo methods I like most are Hidden Markov models and time series methods. I hope to touch on both as this collection matures.

Corrections

If you see mistakes or want to suggest changes, please create an issue on the source repository.

Reuse

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://github.com/rsettlage/rsettlage.github.io, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".