This course is for M.Sc. Statistics and Applied Statistics and Informatics. It is of four credit. 

This course will cover

  • Definition of Stochastic Processes and its classification.
  • Markov Chain, its types. Classification of states. Long run distributions.
  • Discrete state space continuous time Markov chain like Poisson process¬†Birth and death processes, M/M/1, M/M/S queuing models.
  • Renewal and delayed renewal processes.
  • Galton-Watson Binaymi Branching process.
  • Simulation of above discussed Stochastic Processes.

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