Asymptotic and structural properties of special cases of the Wright function arising in probability theory

TL;DR

This paper investigates new asymptotic and structural properties of special Wright functions relevant to probability theory, especially in Poisson-Tweedie mixtures, providing representations, asymptotics, and connections to Bessel functions.

Contribution

It introduces novel asymptotic formulas and structural insights for specific Wright functions, expanding understanding of their behavior in probabilistic models.

Findings

Derived new asymptotic properties for Wright functions with various parameters.

Established integral and structural representations involving well-known special functions.

Connected Wright functions to Bessel functions through reflection principles.

Abstract

This analysis paper presents previously unknown properties of some special cases of the Wright function whose consideration is necessitated by our work on probability theory and the theory of stochastic processes. Specifically, we establish new asymptotic properties of the particular Wright function \[{}_1\Psi_1(\rho,k; \rho,0;x)= \sum_{n=0}^\infty\frac{\Gamma(k+\rho n)}{\Gamma(\rho n)}\,\frac{x^n}{n!}\qquad (|x|<\infty)\] when the parameter $\rho\in (-1,0)\cup (0,\infty)$ and the argument $x$ is real. In the probability theory applications, which are focused on studies of the Poisson-Tweedie mixtures, the parameter $k$ is a non-negative integer. Several representations involving well-known special functions are given for certain particular values of $\rho$. The asymptotics of ${}_1\Psi_1(\rho,k;\rho,0;x)$ are obtained under numerous assumptions on the behavior of the arguments $k$ and $x$ when the parameter $\rho$ is both positive and negative. We also provide some integral representations and structural properties involving the `reduced' Wright function ${}_0\Psi_1(-\!\!\!-; \rho,0;x)$ with $\rho\in (-1,0)\cup (0,\infty)$, which might be useful for the derivation of new properties of members of the power-variance family of distributions. Some of these imply a reflection principle that connects the functions ${}_0\Psi_1(-\!\!\!-; \pm\rho, 0;\cdot)$ and certain Bessel functions. Several asymptotic relationships for both particular cases of this function are also given. A few of these follow under additional constraints from probability theory results which, although previously available, were unknown to analysts.