Course Archives Theoretical Statistics and Mathematics Unit
Course: Markov Chains
Instructor: S Nanda Kishore Reddy
Room: G23
Time: Currently offered
Level: Postgraduate
Syllabus
Past Exams


Syllabus: Finite State Markov Chains. Examples, Classification of States, Stationary Distribution.

Rates of convergence to stationarity, Dirichlet Form and Spectral gap methods, Some Coupling methods with applications, Random walk on Finite Groups, Poisson Processes, Continuous time Markov Chains, Birth-and-death processes.

Suggested Texts :

1. S. M. Ross, Stochastic processes, John Wiley (1996).

2. R. N. Bhattacharya and E. C. Waymire, Stochastic processes with applications.

3. E. GinG, R. Grimmett and L. Saloff-Coste, Lectures on probability theory and statistics,Springer-Verlag (1997)

Evaluation:
Midterm Exam 40 marks
Assignment -- marks
Final Exam 60 marks
Total 100 marks

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Past Exams
Midterm
15.pdf 17.pdf
Semestral
15.pdf 17.pdf
Supplementary and Back Paper
15.pdf

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