I am a currently a student pursuing Masters level course in Data Science.
I am taking a first course on Markov Chains this semester.
I am currently referring to the class handouts and the text book Finite Markov Chain and Algorithmic Application by OLLE Haggstrom.
However, I am really struggling to get an intuitive feed of certain topics.
Could you suggest a more elementary book that slowly builds and spends time on some of the following topics:
- Stationary distribution, Initial distribution( I know the concept, but problems are twisted, so better, deeper understanding is needed)
- Total Variation distance
- Poincare Constant,Poincare Inequality, Cheeger Constant
- Update functions.
- Reversibility
Or in general a source, which covers these topics with but in a more intuitive way with plenty of examples. I am a computer science undergrad and this is one of the first mathematical courses that I am taking.
Cheers!