Poisson Processes

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Poisson Processes Shane G. Henderson http://people.orie.cornell.edu/~shane

description

Poisson Processes. Shane G. Henderson http://people.orie.cornell.edu/~shane. A Traditional Definition. What A re T hey For?. Times of customer arrivals (no scheduling and no groups). Locations, e.g., flaws on wafers, ambulance call locations , submarine locations. - PowerPoint PPT Presentation

Transcript of Poisson Processes

Page 1: Poisson Processes

Poisson ProcessesShane G. Henderson

http://people.orie.cornell.edu/~shane

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Shane G. Henderson

A Traditional Definition

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What Are They For?

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Times of customer arrivals (no scheduling and no groups)

Locations, e.g., flaws on wafers, ambulance call locations,submarine locations

Ambulance call times and locations (3-D)

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“Palm-Khintchine Theorem”

User 1 ★ ★

User 2 ★ ★

User 3 ★

User 4 ★ ★

User n ★ ★

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time

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A Point-Process Definition

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Poisson Point-Processes

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Superposition

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Transformations

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Inversion

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t

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Marking

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t

This “works” because oforder-statistic property

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Thinning

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t

i.i.d.U(0,1)

Thinned points and retained points are in different regions,therefore independent“t” coordinates of retained points are a Poisson process, rate “t” coordinates of thinned points are too, rate

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More on Marking

• Suppose call times for an ambulance follow a Poisson process in time

• Mark each call with the call location (latitude, longitude)

• Resulting 3-D points are those of a Poisson process

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More on Marking

To generate Poisson processes in > 1 dimension, one way is to

– First generate their projection onto a lower dimensional structure (Poisson)

– Independently mark each point with the appropriate conditional distribution

Saltzman, Drew, Leemis, H. (2012). Simulating multivariate non-homogeneous Poisson processes using projections. TOMACS

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This View of Poisson Processes

• Is mathematically elegant• Is highly visual and therefore intuitive• Makes proving many results almost as

easy as falling off a log– Try proving thinned and retained points are

independent Poisson processes• Suggests other generation algorithms

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