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{{Expert-subject|Probability|date=May 2011}}


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In the study of [[stochastic process]]es, '''Palm calculus''', named after Swedish [[teletraffic engineering|teletrafficist]] [[Conny Palm]], is the study of the relationship between [[probability|probabilities]] conditioned on a specified event and time average probabilities. A Palm probability or Palm [[expected value|expectation]], often denoted <math>P^0(\cdot)</math> or <math>E^0[\cdot]</math>, is a probability or expectation conditioned on a specified event occurring at time 0.
 
==Little's formula==
A simple example of a formula from Palm calculus is [[Little's law]] <math>L=\lambda W</math>, which states that the time-average number of users (''L'') in a system is equal to the product of the rate (<math>\lambda</math>) at which users arrive and the Palm-average waiting time (''W'') that a user spends in the system. That is, the average ''W'' gives equal weight to the waiting time of all customers, rather than being the time average of "the waiting times of the customers currently in the system".
 
==Feller's paradox==
An important example of the use of Palm probabilities is Feller's paradox, often associated with the analysis of an [[Pollaczek–Khinchine formula|M/G/1 queue]]. This states that the (time-)average time between the previous and next points in a [[point process]] is greater than the expected interval between points. The latter is the Palm expectation of the former, conditioning on the event that a point occurs at the time of the observation. This paradox occurs because large intervals are given greater weight in the time average than small intervals.
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==PASTA==
A useful result in Palm calculus is that "Poisson arrivals see time averages" (PASTA). That means that, if the event being conditioned on is a point in a [[Poisson process]] (independent of the process being observed), then the distinction between Palm probabilities and time average probabilities can be ignored.
-->
 
==References==
*{{cite journal|last=Le Boudec|first=Jean-Yves|year=2007|title=Understanding the simulation of mobility models with Palm calculus|journal=[[Performance Evaluation]]|volume=64|issue=2|pages=126&ndash;147|doi=10.1016/j.peva.2006.03.001|url=http://lcawww.epfl.ch/Publications/LeBoudec/LeBoudecV04.pdf}}
*Palm, C. (1943) "Intensitätsschwankungen im Fernsprechverkehr" ''Ericsson Techniks'', No. 44 {{MR|11402}}
 
[[Category:Queueing theory]]
[[Category:Stochastic calculus]]
[[Category:Telecommunication theory]]
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Revision as of 01:02, 22 January 2014

Template:Expert-subject

In the study of stochastic processes, Palm calculus, named after Swedish teletrafficist Conny Palm, is the study of the relationship between probabilities conditioned on a specified event and time average probabilities. A Palm probability or Palm expectation, often denoted or , is a probability or expectation conditioned on a specified event occurring at time 0.

Little's formula

A simple example of a formula from Palm calculus is Little's law , which states that the time-average number of users (L) in a system is equal to the product of the rate () at which users arrive and the Palm-average waiting time (W) that a user spends in the system. That is, the average W gives equal weight to the waiting time of all customers, rather than being the time average of "the waiting times of the customers currently in the system".

Feller's paradox

An important example of the use of Palm probabilities is Feller's paradox, often associated with the analysis of an M/G/1 queue. This states that the (time-)average time between the previous and next points in a point process is greater than the expected interval between points. The latter is the Palm expectation of the former, conditioning on the event that a point occurs at the time of the observation. This paradox occurs because large intervals are given greater weight in the time average than small intervals.

References

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  • Palm, C. (1943) "Intensitätsschwankungen im Fernsprechverkehr" Ericsson Techniks, No. 44 Template:MR

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