Math 2.0

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Stochastic Processes XCRZV0WXX1

URIm2://res/XCRZV0WXX1
Kindcourse
CreatorsN. Selvaraju (instructor), S. Dharmaraja (instructor)
MSC60-XX
Scopein
Idscourse 0022nd079:111103022

Expressions

e1: edition

Languageen
Contents
  • part 1: Probability Essentials
  • session 1: Introduction
  • session 2: Random Variables and Probability Distributions
  • session 3: Random Vectors and Expectations
  • session 4: Sequences of Random Variables
  • session 5: References and Exercises 1
  • part 2: Introduction to Stochastic Processes
  • session 6: What are Stochastic Processes?
  • session 7: Classes of Stochastic Processes
  • session 8: References and Exercises 2
  • part 3: Discrete-Time Markov Chains
  • session 9: Introduction and Examples
  • session 10: Classification of States – I
  • session 11: Classification of States – II
  • session 12: Stability of Markov Chains
  • session 13: Reducible Markov Chains
  • session 14: Reversed and Time-Reversible Markov Chains
  • session 15: References and Exercises 3
  • part 4: Continuous-Time Markov Chains
  • session 16: Definition and Kolmogorov Equations
  • session 17: Limiting and Stationary Distributions
  • session 18: Poisson Processes – I
  • session 19: Poisson Processes – II
  • session 20: Birth-Death Processes
  • session 21: M/M/1 Queueing Model
  • session 22: Simple Markovian Queueing Models
  • session 23: References and Exercises 4
  • part 5: Martingales
  • session 24: Filtrations and Conditional Expectations
  • session 25: Conditional Expectations
  • session 26: Generated ?-fields
  • session 27: Martingales, Sub-martingales and Super-martingales
  • session 28: Stopping Times and Inequalities
  • session 29: Convergence Theorems
  • session 30: References and Exercises 5
  • part 6: Brownian Motion
  • session 31: Brownian Motion
  • session 32: Properties of Brownian Motion – I
  • session 33: Properties of Brownian Motion – II
  • session 34: Processes derived from Brownian Motion
  • session 35: Stochastic Differential Equations and Itô Integrals
  • session 36: Itô’s Formula
  • session 37: SDEs and their Applications in Finance
  • session 38: References and Exercises 6
  • part 7: Renewal Processes
  • session 39: Renewal Function and Renewal Equation
  • session 40: Generalized Renewal Processes and Renewal Limit Theorems
  • session 41: Markov Renewal and Markov Regenerative Processes
  • session 42: Non-Markovian Queues
  • session 43: Non-Markovian Queues (contd.) 1
  • session 44: Non-Markovian Queues (contd.) 2
  • session 45: References and Exercises 7
  • part 8: Branching Processes
  • session 46: Galton-Watson Process
  • session 47: Properties of GW Process
  • session 48: Markov Branching Process
  • session 49: References and Exercises 8
  • part 9: Stationary Processes
  • session 50: Stationary Processes
  • session 51: Some Special Stationary Processes
  • session 52: References and Exercises 9

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