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Birth and Death Processes

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Continuous-Time Markov Chains

Part of the book series: Springer Series in Statistics ((SSS))

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Abstract

By a set of birth-death parameters, we shall mean a sequence \(\left\{ {\left( {{\lambda _n},{\mu _n}} \right);n = 0,1,2,...} \right\}\) of pairs of numbers such that \({\lambda _n} > \) for all \(n \geqslant 0,{\mu _n} > 0\) for all \(n \geqslant 1,\), and \({\mu _0} \geqslant 0\). In this chapter, Q will represent the birth and death q-matrix of (3.2.1) given by

$$Q = \left( {\begin{array}{*{20}{c}} { - ({\lambda _0} + {\mu _0})}&{{\lambda _0}} \\ {{\mu _1}}&{ - ({\lambda _1} + {\mu _1})} \\ 0&{{\mu _2}} \\ 0&0 \\ \vdots & \vdots \end{array}\begin{array}{*{20}{c}} 0&0& \cdots \\ 0&0& \cdots \\ {{\lambda _2}}&0& \cdots \\ { - ({\lambda _3} + {\mu _3})}&{{\lambda _3}}& \cdots \end{array}} \right)$$
((1.1))

, where \(\left\{ {\left( {{\lambda _n},{\mu _n}} \right);n = 0,1,2,...} \right\}\) is a set of birth-death parameters. Note again that Q is conservative if and only if μ0 = 0, and that if μ 0 > 0, we are allowing the process to jump from state 0 directly to an absorbing state which, given the context here, is most conveniently labeled as — 1.

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© 1991 Springer-Verlag New York Inc.

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Anderson, W.J. (1991). Birth and Death Processes. In: Continuous-Time Markov Chains. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3038-0_8

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  • DOI: https://doi.org/10.1007/978-1-4612-3038-0_8

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4612-7772-9

  • Online ISBN: 978-1-4612-3038-0

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