Operations Research 13B: Markov Chain n-Step Transition

preview_player
Показать описание
Textbooks:

In this video, I'll talk about how to calculate the n-step transition probabilities of a Markov chain.

----------------------------------------
  1. Yong Wang
  2. stochastic process
  3. Markov Chain
  4. stationary
  5. transition probability
  6. n-step transition
Рекомендации по теме
Operations Research 13B: 0:04:45

Operations Research 13B: Markov Chain n-Step Transition

Operations Research 13A: 0:11:40

Operations Research 13A: Stochastic Process & Markov Chain

Operations Research 13C: 0:06:36

Operations Research 13C: Ergodic Markov Chain

Operations Research 13D: 0:06:59

Operations Research 13D: Markov Chain Steady-State Theorem

Markov Chain Markov 0:09:00

Markov Chain Markov Matrix | Operations Research

Markov Chain 01| 0:29:30

Markov Chain 01| Introduction and Concept | Transition Probability Matrix with Examples| BeingGourav

Markov Chain Practice 0:11:42

Markov Chain Practice 1

Solution of Exercise 0:17:58

Solution of Exercise 8 using Markov Chains

Practice Problems - 0:24:21

Practice Problems - Markov Chain and Decision Tree

First Transition Analysis 0:06:55

First Transition Analysis (First Step Analysis) for Time Between States

Matrix Models for 0:17:31

Matrix Models for Markov Chains

Operations Research 13F: 0:06:13

Operations Research 13F: Absorbing Markov Chain

Estimating the stationary 0:09:38

Estimating the stationary distribution for a Markov chain by sampling

Markov Chains in 0:03:56

Markov Chains in Tennis

Markov chains with 0:09:30

Markov chains with Matrices

Retrospective Higher-Order Markov 0:02:34

Retrospective Higher-Order Markov Processes for User Trails

P. Mascolo - 0:30:42

P. Mascolo - Predicting future state using High Order Markov Chains

10.1 Markov chains 0:12:09

10.1 Markov chains

Workshop: Markov State 0:32:00

Workshop: Markov State Models

Markov Chain Definition 0:09:51

Markov Chain Definition

2301383 Lecture 10 1:10:59

2301383 Lecture 10 Markov Chains: Introduction

Eigenvalue Applications to 0:10:25

Eigenvalue Applications to Markov Chains

Markov Chains l 0:25:26

Markov Chains l Part-1 l Operations Research l Mcom

Markov Chains - 0:04:23

Markov Chains - Sports Analytics Methods

Комментарии
Автор

Hi Guys, please comment and let me know what you think about this Operations Research Open Course. Your feedback is really appreciated. If you enjoy the video, please subscribe and share. All my replies here are only related to the content in my own videos. I am afraid I won't be able to answer other questions. Thanks for your understanding.

YongWang
Автор

Very understandable and clear explanation, thank you !

betulontheway
Автор

On the last slide it should say p11(3)=0.781 but aside from that, thanks for the help

saif
Автор

Great presentation, and greater teaching .. thank you so much 💐

LeilaRmaths
Автор

hello, sir, thanks for your explanation. if i have a scenario: for a state space: [ 0, 1, 2, 3, ...], if i stay in i and i is nonzero state, and i have p probability to move to i+1 state and have 1-p probability to move to i-1 state, if i is zero, then it will return to itself in 1-p and move to 1 in p. so, in this case, i could know that the period of the chain is 1 (aperiodic) since it is irreducible and the period of i is zero is 1, but how to make the stationary distribution exist based on pai *p = pai, and what is the stationary distribution of the chain? i dont know how to find distribution since the chain is infinitive, thank you sir!!!

chowterry
Автор

What if the question asked to know the 25th step?

victormendes
Автор

Very understandable and wonderful explanation. Thank you!

yaseenal-wesabi