
TL;DR
This paper investigates Lamperti-type laws, which are ratios involving stable laws and polynomial tilts, revealing new connections to various distributions and applications in stochastic processes and special functions.
Contribution
It introduces and analyzes Lamperti-type laws, generalizing classical ratios, and uncovers their links to known distributions, integral identities, and stable process properties.
Findings
Derived integral representations for generalized Mittag-Leffler functions
Explicit Levy densities for stable CSBP semigroups
New results on occupation times of Bessel bridges
Abstract
This paper explores various distributional aspects of random variables defined as the ratio of two independent positive random variables where one variable has an -stable law, for , and the other variable has the law defined by polynomially tilting the density of an -stable random variable by a factor . When , these variables equate with the ratio investigated by Lamperti [Trans. Amer. Math. Soc. 88 (1958) 380--387] which, remarkably, was shown to have a simple density. This variable arises in a variety of areas and gains importance from a close connection to the stable laws. This rationale, and connection to the distribution, motivates the investigations of its generalizations which we refer to as Lamperti-type laws. We identify and exploit links to random variables that commonly appear in a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
