Advanced Computational Methods in Stats#
This is a companion webpage to the LTCC course in Advanced Computational Methods in Statistics.
For past year’s materials, see this webpage as a good starting point. See this page for the resources from my undergraduate course, which is largely relevant.
But we will be deviating from the past year’s materials and main resources for this year will be the slides and notebooks.
Slides#
Slides can be found below. I will try to upload them before the lecture (handout version with questions/mini-quizzes excluded).
Please download the slides and open it with Adobe Acrobat if you want to see the animations (activates when you click). They won’t run on your browser.
Lecture 1 (13/11/2023): Introduction to Monte Carlo, Rejection Sampling, Importance Sampling [PDF]
Lecture 2 (20/11/2023): Markov chain Monte Carlo [PDF]
Lecture 3 (27/11/2023): Introduction to stochastic filtering, smoothing, and particle filters [PDF]
Lecture 4 (04/12/2023): Particle filters and smoothers, parameter estimation in SSMs [PDF]
Lecture 5 (11/12/2023): Bayesian estimation in SSMs, theory of particle filters [PDF]