A Short History of Markov Chain Monte Carlo: Subjective Recollections from Incomplete Data

TL;DR

This paper traces the historical development of Markov Chain Monte Carlo (MCMC) from its origins in the 1940s to its current applications, highlighting how it transformed problem-solving and thinking in statistics.

Contribution

It provides a subjective historical overview of MCMC's evolution and its impact on statistical methodology and problem-solving approaches.

Findings

MCMC originated in the late 1940s and evolved through various stages.

The development of MCMC significantly changed problem-solving strategies.

MCMC has influenced the way statisticians conceptualize complex problems.

Abstract

We attempt to trace the history and development of Markov chain Monte Carlo (MCMC) from its early inception in the late 1940s through its use today. We see how the earlier stages of Monte Carlo (MC, not MCMC) research have led to the algorithms currently in use. More importantly, we see how the development of this methodology has not only changed our solutions to problems, but has changed the way we think about problems.