Results 251 to 260 of about 15,413,531 (300)

Multivariate Phase-Type Distributions

Operations Research, 1984
A (univariate) random variable is said to be of phase type if it can be represented as the time until absorption in a finite state absorbing Markov chain. Univariate phase type random variables are useful because they arise from processes that are often encountered in applications, they have densities that can be written in a closed form, they possess
David Assaf, Naftali A. Langberg, Thomas H. Savits, Moshe Shaked   +3 more
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Phase-Type Distributions

2017
The class of distributions on [0, ∞) having a rational Laplace transform (i.e., a Laplace transform that is the fraction between two polynomials) will, for reasons that will become apparent in the next chapter, be referred to as matrix-exponential distributions.
Mogens Bladt, Bo Friis Nielsen
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Approximation of Discrete Phase-Type Distributions

38th Annual Simulation Symposium, 2005
The analysis of discrete stochastic models such as generally distributed stochastic Petri nets can be done using state space-based methods. The behavior of the model is described by a Markov chain that can be solved mathematically. The phase-type distributions that are used to describe non-Markovian distributions have to be approximated.
Claudia Isensee, Graham Horton
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Variational Bayes for Phase-Type Distribution

Communications in Statistics - Simulation and Computation, 2014
This article develops an algorithm for estimating parameters of general phase-type (PH) distribution based on Bayes estimation. The idea of Bayes estimation is to regard parameters as random variables, and the posterior distribution of parameters which is updated by the likelihood function provides estimators of parameters.
Hiroyuki Okamura, Ryo Watanabe, Tadashi Dohi   +2 more
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Bilateral phase‐type distributions

Naval Research Logistics Quarterly, 1985
AbstractIn this article we define a class of distributions called bilateral phase type (BPH), and study its closure and computational properties. The class of BPH distributions is closed under convolution, negative convolution, and mixtures. The one‐sided version of BPH, called generalized phase type (GPH), is also defined.
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Phase-Type Distributions

2014
Continuous-time Markov chainsContinuous-time Markov chain (CTMCs)CTMC seealso Continuous-time Markov chain Markov chain seealso Continuous-time Markov chain are a class of stochastic processes with a discrete state space in which the time between transitions follows an exponential distribution.
Peter Buchholz, Jan Kriege, Iryna Felko
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Graph-based algorithms for phase-type distributions

Statistics and Computing, 2022
Abstract Phase-type distributions model the time until absorption in continuous or discrete-time Markov chains on a finite state space. The multivariate phase-type distributions have diverse and important applications by modeling rewards accumulated at visited states.
Tobias Røikjer, Asger Hobolth, Kasper Munch   +2 more
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Multivariate finite-support phase-type distributions

Journal of Applied Probability, 2020
AbstractWe introduce a multivariate class of distributions with support I, a k-orthotope in $[0,\infty)^{k}$ , which is dense in the set of all k-dimensional distributions with support I. We call this new class ‘multivariate finite-support phase-type distributions’ (MFSPH). Though we generally define MFSPH distributions on any finite k-orthotope in $[
Celeste R. Pavithra, T. G. Deepak
openaire   +3 more sources