This video is part of a series of lectures on Markov Chains (a subset of a series on Stochastic Processes) aimed at individuals with some background in statistical modelling, computing, and linear algebra. To see where this lecture fits on the asynchronous learning tree, follow: drive.google.com/file/d/1idu1...
This work by Etienne A.D. Pienaar is licensed under CC BY-NC-ND 4.0.
References:
Ross, S.M., Kelly, J.J., Sullivan, R.J., Perry, W.J., Mercer, D., Davis, R.M., Washburn, T.D., Sager, E.V., Boyce, J.B. and Bristow, V.L., 1996. Stochastic processes (Vol. 2). New York: Wiley.
Stirzaker, D., 1999. Probability and random variables: a beginner's guide. Cambridge University Press.
Zucchini, W., MacDonald, I.L. and Langrock, R., 2017. Hidden Markov models for time series: an introduction using R. CRC press.
Software and Packages:
R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL www.R-project.org/.
Useful Links:
None.
Materials:
drive.google.com/drive/folder...
Errata (if any):
docs.google.com/document/d/1H...