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While the exponential distribution is the continuous analogue of the geometric distribution, the hyperexponential distribution is not analogous to the hypergeometric distribution. The hyperexponential distribution is an example of a mixture density.
The hyperexponential distribution in probability. Tetration, also known as hyperexponentiation. This page was last edited on 4 ...
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In probability theory and statistics, the exponential distribution or negative exponential distribution is the probability distribution of the distance between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate; the distance parameter could be any meaningful mono-dimensional measure of the process, such as time ...
The standard deviation of an exponential distribution is equal to its mean, so its coefficient of variation is equal to 1. Distributions with CV < 1 (such as an Erlang distribution) are considered low-variance, while those with CV > 1 (such as a hyper-exponential distribution) are considered high-variance [citation needed].
The Erlang distribution is a series of k exponential distributions all with rate . The hypoexponential is a series of k exponential distributions each with their own rate λ i {\displaystyle \lambda _{i}} , the rate of the i t h {\displaystyle i^{th}} exponential distribution.
A phase-type distribution is a probability distribution constructed by a convolution or mixture of exponential distributions. [1] It results from a system of one or more inter-related Poisson processes occurring in sequence , or phases.
The distribution thus defined, and any of its multiples, is called a Mittag-Leffler distribution of order . All these probability distributions are absolutely continuous . Since E 1 {\displaystyle E_{1}} is the exponential function, the Mittag-Leffler distribution of order 1 {\displaystyle 1} is an exponential distribution .