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12:19
Markov Chains - Part 1
Part 2: http://www.youtube.com/watch?v=jtHBfLtMq4U In this video, I discuss Markov Chains,...
published: 13 Jan 2010
author: patrickJMT
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52:06
16. Markov Chains I
MIT 6.041 Probabilistic Systems Analysis and Applied Probability, Fall 2010 View the compl...
published: 09 Nov 2012
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29:29
Finite Math: Introduction to Markov Chains
Finite Math: Introduction to Markov Chains. In this video we discuss the basics of Markov ...
published: 05 Nov 2012
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46:38
Lecture 31: Markov Chains | Statistics 110
We introduce Markov chains -- a very beautiful and very useful kind of stochastic process ...
published: 29 Apr 2013
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47:01
Lecture 33: Markov Chains Continued Further | Statistics 110
We continue to explore Markov chains, and show how Google PageRank can be understood in te...
published: 29 Apr 2013
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4:28
Introduction to Markov Chains
In this video I describe a basic Discrete Markov Chain (http://en.wikipedia.org/wiki/Marko...
published: 20 Sep 2012
author: Jason Young
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20:26
Finite Math: Markov Chain Example - The Gambler's Ruin
Finite Math: Markov Chain Example - The Gambler's Ruin. In this video we look at a very co...
published: 16 Nov 2012
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67:10
Mod-01 Lec-10 Markov Chain
Performance Evaluation of Computer Systems by Prof.Krishna Moorthy Sivalingam, Department ...
published: 25 Jul 2012
author: nptelhrd
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8:34
Markov Chains, Part 3 - Regular Markov Chains
Part 4: http://www.youtube.com/watch?v=31X-M4okAI0 Markov Chains, Part 3. In this video, I...
published: 27 Aug 2012
author: patrickJMT
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10:52
Markov Chain Matlab Tutorial--part 1
Hello! Here's a detailed tutorial on markov models conceptually and with example computati...
published: 24 Aug 2012
author: Student Dave
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4:11
Markov Chains Transition Matrices
Basics of Markov chains....
published: 18 Feb 2013
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14:43
(ML 14.2) Markov chains (discrete-time) (part 1)
Definition of a (discrete-time) Markov chain, and two simple examples (random walk on the ...
published: 07 Jul 2011
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7:15
Markov chains (Language of Coins: 11/16)
What motivated the concept of Markov Chains? Featuring Plato's theory of forms, Jacob Bern...
published: 26 Jun 2013
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30:20
Finite Math: Markov Chain Steady-State Calculation
Finite Math: Markov Chain Steady-State Calculation. In this video we discuss how to find t...
published: 14 Nov 2012
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35:35
Markov Chain Monte Carlo and the Metropolis Alogorithm
An introduction to the intuition and implementation of the Metropolis algorithm....
published: 05 May 2012
author: Jeff Picton
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53:05
Mod-01 Lec-12 Continuous time Markov chain and queuing theory-I
Performance Evaluation of Computer Systems by Prof.Krishna Moorthy Sivalingam, Department ...
published: 25 Jul 2012
author: nptelhrd
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16:23
Basics of Markov Chains Example 1
This example demonstrates how to solve a Markov Chain problem....
published: 02 May 2011
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51:50
18. Markov Chains III
MIT 6.041 Probabilistic Systems Analysis and Applied Probability, Fall 2010 View the compl...
published: 09 Nov 2012
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62:24
Ian Fellows - How to solve (almost) any problem using Markov Chain Monte Carlo
MCMC sampling has allowed for simulation from complex, massively multivariate distribution...
published: 10 May 2013
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79:04
Markov Chain Monte Carlo
PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning View the talk ...
published: 06 Dec 2012
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13:40
MCMC Markov Chain Monte Carlo demos with Matlab
http://quantlabs.net/blog/2014/04/mcmc-markov-chain-monte-carlo-demos-with-matlab/...
published: 10 Apr 2014
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21:48
Finite Math: Long-run Markov Chain Probabilities
Finite Math: Long-run Markov Chain Probabilities. *Small Correction at the 9:18 mark - the...
published: 12 Nov 2012
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1:32
Recurrent and Transient States in Markov Chains
In this mini-lesson, the notions of transient and recurrent states in Markov Chains are in...
published: 17 Jun 2014
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12:46
(ML 18.4) Examples of Markov chains with various properties (part 1)
A very simple example of a Markov chain with two states, to illustrate the concepts of irr...
published: 25 Jul 2011
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A Markov chain, named after Andrey Markov, is a mathematical system that undergoes transitions from one state to another, between a finite or countable number of possible states. It is a random process characterized as memoryless: the next state depends only on the current state and not on the sequence of events that preceded it. This specific kind of "memorylessness" is called the Markov property. Markov chains have many applications as statistical models of real-world processes.

Formally, a Markov chain is a random process with the Markov property. Often, the term "Markov chain" is used to mean a Markov process which has a discrete (finite or countable) state-space. Usually a Markov chain is defined for a discrete set of times (i.e., a discrete-time Markov chain) although some authors use the same terminology where "time" can take continuous values. The use of the term in Markov chain Monte Carlo methodology covers cases where the process is in discrete time (discrete algorithm steps) with a continuous state space. The following concentrates on the discrete-time discrete-state-space case.




This page contains text from Wikipedia, the Free Encyclopedia - http://en.wikipedia.org/wiki/Markov_chain

This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.