Hyperexponential distribution

Introduction

Published in Joseph Y.-T. Leung, Handbook of SCHEDULING, 2004

Shanthikumar and Sumita [42] show that if Is≅1, the distribution of time spent in the shop is closely approximated by an exponential distribution, if Is≪1, the distribution is best approximated by a generalized Erlang distribution, and if Is≫1, the distribution is best approximated by a hyperexponential distribution. They then apply the results of Seidmann and Smith [29] to quote CON due dates to minimize the expected cost of the system.

Bayesian Inference of the Phase-Type Stress-Strength Reliability Models

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Journal Information

Published in American Journal of Mathematical and Management Sciences, 2023

Joby K. Jose, M. Drisya, Sebastian George

Hyper-exponential distribution is the mixture of a finite number of independent exponential distributions. Let be k independent random variables then follows hyper-exponential distribution, where is the mixing density such that This is a CPH distribution with representation where and

Hyperexponential distribution

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Introduction

Bayesian Inference of the Phase-Type Stress-Strength Reliability Models