Continuous scaled phase-type distributions
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Products between phase-type distributed random variables and any independent, positive and continuous random variable are studied. Their asymptotic properties are established, and an expectation-maximization algorithm for their effective statistical inference is derived and implemented using real-world datasets. In contrast to discrete scaling studied in earlier literature, in the present continuous case closed-form formulas for various functionals of the resulting distributions are obtained, which facilitates both their analysis and implementation. The resulting mixture distributions are very often heavy-tailed and yet retain various properties of phase-type distributions, such as being dense (in weak convergence) on the set of distributions with positive support.
Original language | English |
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Journal | Stochastic Models |
Volume | 39 |
Issue number | 2 |
Pages (from-to) | 293-322 |
ISSN | 1532-6349 |
DOIs | |
Publication status | Published - 2023 |
Bibliographical note
Publisher Copyright:
© 2022 The Author(s). Published with license by Taylor and Francis Group, LLC.
- Heavy tails, parameter estimation, phase-type, scale mixtures
Research areas
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