Learn · Discrete-time Markov Chains And Poisson Processes
Lecture 14 of 35Week 4: Classification of States
Lec 14: Number of Visits
Prof. Ayon Ganguly and Prof. Subhamay Saha · IIT Guwahati
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- Discrete-time Markov Chains And Poisson Processes, IIT Guwahati (at NPTEL)
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- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
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- Tweens profiles and older. How courses are placed
All the lectures
- Lec 1: Review of Basic Probability I
- Lec 2: Review of Basic Probability II
- Lec 3: Review of Basic Probability III
- Lec 4: Stochastic Processes
- Lec 5: Definition of Markov Chain and Transition Probabilities
- Lec 6: Markov Property and Chapman-Kolmogorov Equations
- Lec 7: Chapman-Kolmogorov Equations: Examples
- Lec 8: Accessibility and Communication of States
- Lec 9: Hitting Time I
- Lec 10: Hitting Time II
- Lec 11: Hitting Time III
- Lec 12: Strong Markov Property
- Lec 13: Passage Time and Excursion
- Lec 14: Number of Visits
- Lec 15: Class Property
- Lec 16: Transience and Recurrence of Random Walks
- Lec 17: Stationary Distribution I
- Lec 18: Stationary Distribution II
- Lec 19: Stationary Distribution III
- Lec 20: Limit Theorems I
- Lec 21: Limit Theorems II
- Lec 22: Some Problems I
- Lec 23: Some Problems II
- Lec 24: Time Reversibility
- Lec 25: Properties of Exponential Distribution
- Lec 26: Some Problems
- Lec 27: Order Statistics
- Lec 28: Poisson Processes
- Lec 29: Poisson Thinning I
- Lec 30: Poisson Thinning II
- Lec 31: Conditional Arrival Times
- Lec 32: Independent Poisson Processes
- Lec 33: Some Problems
- Lec 34: Compound Poisson Processes
- Live Session 15-03-2022