An introduction to importance sampling - optimal importance distributions @SpartacanUsuals
An introduction to importance sampling - optimal importance distributions @SpartacanUsuals
Uploaded May 2018 | Updated September 2026, 1 hour ago
This video continues the introduction to importance sampling by discussing how the variance of these estimators depends crucially on the choice of importance distribution.

This video is part of a lecture course which closely follows the material covered in the book, "A Student's Guide to Bayesian Statistics", published by Sage, which is available to order on Amazon here: amazon.co.uk/Students-Guide-Bayesian-Statistics/dp/1473916364

For more information on all things Bayesian, have a look at: ben-lambert.com/bayesian/. The playlist for the lecture course is here: youtube.com/playlist?list=PLwJRxp3blEvZ8AKMXOy0fc0cqT61GsKCG&disable_polymer=true
An introduction to importance sampling - optimal importance distributionsAn introduction to continuous marginal probability distributionsHow to check if treatment is randomly assigned?Estimating the error variance in matrix form - part 6Variance-covariance matrix using matrix notation of factor analysisIntroduction to the matrix formulation of econometricsAn introduction to Jeffreys priors - 3Sample balancing via stratification and matchingModel implied variance-covariance matrix of indicators (matrix form) - part 1An introduction to the Poisson distribution - 1Effective sample size: representing the cost of dependent samplingMaximum likelihood: Normal error distribution - estimator variance part 1
Ben Lambert |

An introduction to importance sampling - optimal importance distributions

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