{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

Markov_chainsI_beamer

# Markov_chainsI_beamer - Introductory Engineering Stochastic...

This preview shows pages 1–9. Sign up to view the full content.

Introductory Engineering Stochastic Processes, ORIE 361 Instructor: Mark E. Lewis, Associate Professor School of Operations Research and Information Engineering Cornell University Markov Chains – Introduction 1/ 11

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Stochastic Processes A stochastic process is a sequence of random variables indexed by time. 2/ 11
Stochastic Processes A stochastic process is a sequence of random variables indexed by time. The value of each random variable usually represents the state of some process. The set of all possible states (for all time is called the state space . 2/ 11

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Stochastic Processes A stochastic process is a sequence of random variables indexed by time. The value of each random variable usually represents the state of some process. The set of all possible states (for all time is called the state space . If we follow a realization of a stochastic process for all time, it is called a sample path of the process. 2/ 11
Stochastic Processes A stochastic process is a sequence of random variables indexed by time. The value of each random variable usually represents the state of some process. The set of all possible states (for all time is called the state space . If we follow a realization of a stochastic process for all time, it is called a sample path of the process. Dow Jones Industrial Average (DJIA) graphed over time 2/ 11

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Stochastic Processes A stochastic process is a sequence of random variables indexed by time. The value of each random variable usually represents the state of some process. The set of all possible states (for all time is called the state space . If we follow a realization of a stochastic process for all time, it is called a sample path of the process. Dow Jones Industrial Average (DJIA) graphed over time Daily inventory levels 2/ 11
Stochastic Processes A stochastic process is a sequence of random variables indexed by time. The value of each random variable usually represents the state of some process. The set of all possible states (for all time is called the state space . If we follow a realization of a stochastic process for all time, it is called a sample path of the process. Dow Jones Industrial Average (DJIA) graphed over time Daily inventory levels Before viewing the process, the path is unknown. After viewing some portion of the path, ( X 1 , X 2 , . . . , X n ) or { X s , s t } is called the history up until time n or t , respectively. 2/ 11

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Stochastic Processes A stochastic process is a sequence of random variables indexed by time.
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}