Introduction to MCMC

By Anthony N. Pettitt, Candice M. Hincksman. 2012

75 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Mathematical Physics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/6b5479a577b24607acf4f3ab9ce3714233032a25

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

1. Ioannis Kontoyiannis
2. David M. Blei
3. Samuel J. Gershman
4. Petros Dellaportas

In Mathematical Physics

1. Petros Dellaportas
2. Ioannis Kontoyiannis
3. David M. Blei
4. Samuel J. Gershman

In Statistics and Probability

1. Samuel J. Gershman
2. David M. Blei
3. Petros Dellaportas
4. Ioannis Kontoyiannis
5. Qiang Liu
6. Rajesh Ranganath
7. Dustin Tran
8. Charles Sutton

Citations in the corpus

• A Tutorial on Bayesian Nonparametric Models (2011, methodology): “The idea MCMC methods is to define a Markov chain on the hidden variables that has the posterior as its equilibrium distribution (Andrieu et al., 2003).”
• Control variates for estimation based on reversible Markov chain Monte Carlo samplers (2012, background): “(Such densities are commonly met in, for example, spatial statistics; see Dellaportas and Roberts (2003) for an illustrative example.)”