Why we typically use dependent sampling to sample from the posterior @SpartacanUsuals
Why we typically use dependent sampling to sample from the posterior @SpartacanUsuals
Uploaded May 2018 | Updated September 2026, 2 hours ago
Explains why independent sampling from the posterior is typically impossible and why we are forced to use dependent sampling instead.

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
Why we typically use dependent sampling to sample from the posteriorAn introduction to the Poisson distribution - 2Score test (Lagrange Multiplier test) - introductionRepresenting heteroscedasticity in matrix formWhat is meant by overfitting?Estimating the error variance in matrix form - part 1Bayesian posterior samplingAn introduction to Gibbs samplingMaximum Likelihood: Bernoulli random variables estimator variance part 2An introduction to importance sampling - optimal importance distributionsAn introduction to continuous marginal probability distributionsHow to check if treatment is randomly assigned?
Ben Lambert |

Why we typically use dependent sampling to sample from the posterior

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