Markov Chain Monte Carlo methods

June 28, 2020 — October 28, 2020

Bayes
estimator distribution
Markov processes
Monte Carlo
probabilistic algorithms
probability
Figure 1

TBD. Sampling from approximate distributions by reweighting. I mostly use it in particle filters.

Art Owen’s Importance sampling chapter.

Figure 2

1 References

Ben Rached, Nadhir, Botev, Kammoun, et al. 2018. Importance Sampling Estimator of Outage Probability Under Generalized Selection Combining Model.” In Proc of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Ben Rached, N., Kammoun, Alouini, et al. 2016. Unified Importance Sampling Schemes for Efficient Simulation of Outage Capacity over Generalized Fading Channels.” IEEE Journal of Selected Topics in Signal Processing.
Blanchet, and Lam. 2012. State-Dependent Importance Sampling for Rare-Event Simulation: An Overview and Recent Advances.” Surveys in Operations Research and Management Science.
Botev, L’Ecuyer, and Tuffin. 2013. Markov Chain Importance Sampling with Applications to Rare Event Probability Estimation.” Statistics and Computing.
Burda, Grosse, and Salakhutdinov. 2016. Importance Weighted Autoencoders.” In arXiv:1509.00519 [Cs, Stat].
Cremer, Morris, and Duvenaud. 2017. Reinterpreting Importance-Weighted Autoencoders.” In ICLR 2017.
Hadjis, and Ermon. n.d. Importance Sampling over Sets: A New Probabilistic Inference Scheme.”
Kappen, and Ruiz. 2016. Adaptive Importance Sampling for Control and Inference.” Journal of Statistical Physics.
Karampatziakis, and Langford. 2010. Online Importance Weight Aware Updates.” arXiv:1011.1576 [Cs].
Kong, Augustine. 1992. A Note on Importance Sampling Using Standardized Weights.”
Kong, A. 2014. Importance Sampling.” In Wiley StatsRef: Statistics Reference Online.
Liu. 1996. Metropolized Independent Sampling with Comparisons to Rejection Sampling and Importance Sampling.” Statistics and Computing.
Pesenti, Bettini, Millossovich, et al. 2020. Scenario Weights for Importance Measurement (SWIM) – An R Package for Sensitivity Analysis.” SSRN Scholarly Paper ID 3515274.
Shahabuddin. 1994. Importance Sampling for the Simulation of Highly Reliable Markovian Systems.” Management Science.
Srinivasan. 2013. Importance Sampling: Applications in Communications and Detection.
Vehtari, Simpson, Gelman, et al. 2019. Pareto Smoothed Importance Sampling.” arXiv:1507.02646 [Stat].
Virrion. 2020. Deep Importance Sampling.” arXiv:2007.02692 [q-Fin].