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Markov arrival process : ウィキペディア英語版
Markovian arrival process

In queueing theory, a discipline within the mathematical theory of probability, a Markovian arrival process (MAP or MArP) is a mathematical model for the time between job arrivals to a system. The simplest such process is a Poisson process where the time between each arrival is exponentially distributed.
The processes were first suggested by Neuts in 1979.〔
==Definition==

A Markov arrival process is defined by two matrices ''D''0 and ''D''1 where elements of ''D''0 represent hidden transitions and elements of ''D''1 observable transitions. The block matrix ''Q'' below is a transition rate matrix for a continuous-time Markov chain.
:
Q=\left(& \vdots & \ddots & \ddots & \ddots
\end\right
)\; .
The simplest example is a Poisson process where ''D''0 = −''λ'' and ''D''1 = ''λ'' where there is only one possible transition, it is observable and occurs at rate ''λ''. For ''Q'' to be a valid transition rate matrix, the following restrictions apply to the ''D''''i''
:\begin
0\leq ()_&<\infty \\
0\leq ()_&<\infty \quad i\neq j \\
\, ()_&<0 \\
(D_+D_)\boldsymbol &= \boldsymbol
\end

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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