Michael K. Pitt

Statistics and Probability · 1999–2015

A researcher in the Science corpus: 7 papers; trusts 22 researchers and is trusted by 145 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 33 citations into it; #3,147 of 12,932 by trust here, #1,887 by citations
• Artificial Intelligence — 28 citations into it; #12,503 of 35,345 by trust here, #13,544 by citations
• Probabilistic & Bayesian Methods — 16 citations into it; #118 of 1,525 by trust here, #192 by citations
• Economics and Econometrics — 7 citations into it
• Finance — 5 citations into it; #4,310 of 10,518 by trust here, #3,859 by citations

Whom Michael K. Pitt trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Christophe Andrieu
2. Lars Peter Hansen
3. MARK A. Beaumont
4. Adrian F. M. Smith
5. Gareth O. Roberts
6. Arnaud Doucet
7. Neil J. Gordon
8. Pierre Del Moral
9. Nicolas Chopin
10. Jun S. Liu

Who trusts Michael K. Pitt overall

1. Sebastian Thrun
2. Arnaud Doucet
3. Fredrik Lindsten
4. Siddhartha Chib
5. Garland B. Durham
6. Dieter Fox
7. Paul Fearnhead
8. Maja Pantic
9. Nicolas Chopin
10. Christophe Andrieu

Papers from Michael K. Pitt's perspective

Ordered by how strongly the researchers Michael K. Pitt trusts endorse each paper. Same corpus, a different order for every researcher.

1. Monte Carlo strategies in scientific computing
2. Improved particle filter for nonlinear problems
3. Following a moving target—Monte Carlo inference for dynamic Bayesian models
4. Weak convergence and optimal scaling of random walk Metropolis algorithms
5. Particle Markov chain Monte Carlo methods
6. Annealed importance sampling
7. Estimation of population growth or decline in genetically monitored populations.
8. Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
9. Bayesian analysis of binary and polychotomous response data
10. Convergence properties of pseudo-marginal Markov chain Monte Carlo algorithms

Their papers

• On some properties of Markov chain Monte Carlo simulation methods based on the particle filter (2012) — 297 citations
• Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator (2012) — 322 citations
• The correlated pseudomarginal method (2015) — 106 citations
• Efficient Bayesian inference for Gaussian copula regression models (2006) — 289 citations
• Importance Sampling Squared for Bayesian Inference in Latent Variable Models (2013) — 57 citations
• Constructing First Order Stationary Autoregressive Models via Latent Processes (2002) — 57 citations
• Filtering via Simulation: Auxiliary Particle Filters (1999)