1,602 research outputs found

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

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    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 1Ψ1(ρ, k; ρ, 0; x) = X∞ n=0 Γ(k + ρn) Γ(ρn) x n n! (|x| <∞) when the parameter ρ ∈ (−1, 0)∪(0, ∞) 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 ρ. The asymptotics of 1Ψ1(ρ, k; ρ, 0; x) are obtained under numerous assumptions on the behavior of the arguments k and x when the parameter ρ is both positive and negative. We also provide some integral representations and structural properties involving the ‘reduced’ Wright function 0Ψ1(−−; ρ, 0; x) with ρ ∈ (−1, 0) ∪ (0, ∞), 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 0Ψ1(−−;±ρ, 0; ·) 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

    On Poisson–Tweedie mixtures

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    Poisson-Tweedie mixtures are the Poisson mixtures for which the mixing measure is generated by those members of the family of Tweedie distributions whose support is non-negative. This class of non-negative integer-valued distributions is comprised of Neyman type A, back-shifted negative binomial, compound Poisson-negative binomial, discrete stable and exponentially tilted discrete stable laws. For a specific value of the “power” parameter associated with the corresponding Tweedie distributions, such mixtures comprise an additive exponential dispersion model. We derive closed-form expressions for the related variance functions in terms of the exponential tilting invariants and particular special functions. We compare specific Poisson-Tweedie models with the corresponding Hinde-Demétrio exponential dispersion models which possess a comparable unit variance function. We construct numerous local approximations for specific subclasses of Poisson-Tweedie mixtures and identify Lévy measure for all the members of this three-parameter family

    Local approximations for branching particle systems

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    New properties and representations for members of the power-variance family. II

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    This is the continuation of [V. Vinogradov, R.B. Paris, and O. Yanushkevichiene, New properties and representations for members of the power-variance family. I, Lith. Math. J., 52(4):444–461, 2012]. Members of the powervariance family of distributions became popular in stochastic modeling which necessitates a further investigation of their properties. Here, we establish Zolotarev duality of the refined saddlepoint-type approximations for all members of this family, thereby providing an interpretation of the Letac–Mora reciprocity of the corresponding NEFs. Several illustrative examples are given. Subtle properties of related special functions are established.An erratum to this article is available at 10.1007/s10986-014-9240-1

    Branching particle systems and compound Poisson processes related to PĂłlya-Aeppli distributions

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    We establish numerous new refined local limit theorems for a class of compound Poisson processes with Pólya-Aeppli marginals, and for a particular family of the branching particle systems which undergo critical binary branching and can be approximated by the backshifted Feller diffusion. To this end, we also derive new results for the families of Pólya–Aeppli and Poisson–exponential distributions. We relate a few of them to properties of certain special functions some of which were previously unknown

    On two extensions of the canonical Feller–Spitzer distribution

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    We introduce two extensions of the canonical Feller–Spitzer distribution from the class of Bessel densities, which comprise two distinct stochastically decreasing one-parameter families of positive absolutely continuous infinitely divisible distributions with monotone densities, whose upper tails exhibit a power decay. The densities of the members of the first class are expressed in terms of the modified Bessel function of the first kind, whereas the members of the second class have the densities of their Lévy measure given by virtue of the same function. The Laplace transforms for both these families possess closed–form representations in terms of specific hypergeometric functions. We obtain the explicit expressions by virtue of the particular parameter value for the moments of the distributions considered and establish the monotonicity of the mean, variance, skewness and excess kurtosis within the families. We derive numerous properties of members of these classes by employing both new and previously known properties of the special functions involved and determine the variance function for the natural exponential family generated by a member of the second class

    The evaluation of a weighted sum of Gauss hypergeometric functions and its connection with Galton–Watson processes

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    We evaluate a weighted sum of Gauss hypergeometric functions for certain ranges of the argument, weights and parameters. We establish the domain of absolute convergence of this series by determining the growth of the hypergeometric function for large summation index. We present an application to Galton–Watson branching processes arising in the theory of stochastic processes. We introduce a new class of positive integer-valued distributions with power tails

    Regional geographic information systems of health and environmental monitoring

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    The article describes a new scientific and methodological approach to designing geographic information systems of health and environmental monitoring for urban areas. Geographic information systems (GIS) are analytical tools of the regional health and environmental monitoring; they are used for an integrated assessment of the environmental status of a large industrial centre or a part of it. The authors analyse the environmental situation in Voronezh, a major industrial city, located in the Central Black Earth Region with a population of more than 1 million people. The proposed research methodology is based on modern approaches to the assessment of health risks caused by adverse environmental conditions. The research work was implemented using a GIS and multicriteria probabilistic and statistical evaluation to identify cause-and-effect links, a combination of action and reaction, in the dichotomy "environmental factors - public health". The analysis of the obtained statistical data confirmed an increase in childhood diseases in some areas of the city. Environmentally induced diseases include congenital malformations, tumors, endocrine and urogenital pathologies. The main factors having an adverse impact on health are emissions of carcinogens into the atmosphere and the negative impact of transport on the environment. The authors identify and characterize environmentally vulnerable parts of the city and developed principles of creating an automated system of health monitoring and control of environmental risks. The article offers a number of measures aimed at the reduction of environmental risks, better protection of public health and a more efficient environmental monitoring
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