Transcription of Chapter 1 Markov Chains - Yale University
{{id}} {{{paragraph}}}
Example: marketing
Chapter 1 Markov Chains - Yale University
Chapter 1 Markov ChainsA sequence of random variablesX0,X1,..with values in a countable setSisa Markov chain if at any timen, the future states (or values)Xn+1,Xn+2,..depend on the historyX0,..,Xnonly through the present are fundamental stochastic processes that have many diverse applica-tions. This is because a Markov chain represents any dynamical system whosestates satisfy the recursionXn=f(Xn 1,Yn),n 1, whereY1, and identically distributed ( ) andfis a deterministic func-tion. That is, the new stateXnis simply a function of the last state andan auxiliary random variable. Such system dynamics are typical of those forqueue lengths in call centers, stresses on materials, waiting times in produc-tion and service facilities, inventories in supply Chains , parallel-processingsoftware, water levels in dams, insurance funds, stock prices, Chapter begins by describing the basic structure of a Markov chainand how its single-step transition probabilities determine its evolution.
Chapter 1 Markov Chains ... chains are fundamental stochastic processes that have many diverse applica- ... what is the probability of reaching a certain state, ...
Loading..
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document:
Related search queries
Probability & Stochastic Processes, Probability, Lectures: Probability, Statistics and Stochastic Processes, Probability and Stochastic Processes, Stochastic processes, Stochastic, Probability, Statistics, and Random Processes, Random processes for electrical engineering, Probability, Statistics, and Stochastic Processes, Probability Random Variables and Stochastic, Processes