Stochastic processes with orthogonal polynomial eigenfunctions

Markov processes which are reversible with either Gamma, Normal, Poisson or Negative Binomial stationary distributions in the Meixner class and have orthogonal polynomial eigenfunctions are characterized as being processes subordinated to well-known diffusion processes for the Gamma and Normal, and birth and death processes for the Poisson and Negative Binomial. A characterization of Markov processes with Beta stationary distributions and Jacobi polynomial eigenvalues is also discussed.     

Optimal transportation-entropy inequalities for several usual distributions on ℝ

In this paper,based on the recent results of Gozlan and Léonard we give optimal transportationentropy inequalities for several usual distributions on R,such as Bernoulli,Binomial,Poisson,Gamma distributions and infinitely divisible distributions with positive or negative jumps.     

Bounds for the difference between median and mean of gamma and poisson distributions

We use elementary methods and the Poisson-Gamma relationship to obtain bounds for the difference between median and mean of Gamma and Poisson distributions.     

基于贝叶斯分析的中国商业银行内部欺诈分析

内部欺诈事件类型是中国商业银行最严重的操作风险类型。但由于操作风险本质特征和中国商业银行内部欺诈损失数据收集年度较短,数据匮乏,小样本数据容易导致参数结果不稳定。为了在小样本数据下进行更准确的度量,本文采用贝叶斯马尔科夫蒙特卡洛模拟方法,在损失分布法框架下,假设损失频率服从泊松-伽马分布,而损失强度服从广义帕累托-混合伽马分布,分析后验分布的形式,获得中国商业银行不同业务线的内部欺诈损失频率和损失强度的后验分布估计,并进行蒙特卡罗模拟获得不同业务线内部欺诈的风险联合分布。结果表明,拟合结果很好,与传统极值分析法相比,基于利用贝叶斯的分析获得的后验分布可以作为未来的先验分布,有利于在较小样本下获得较真实的参数估计,本方法有助于银行降低监管资本要求。     

Orthogonal Spaces Associated with Exponentials of Indicator Functions on Fock Space

Parthasarathy and Sunder have proved that the set of coherentvectors associated with the indicator functions of Borel setsis total in the boson Fock space (L²(R⁺;C)). The paper studiesthe space generated by coherent vectors associated with theunion of n intervals. A complete characterization is given oftheir orthogonal space in terms of their chaos expansion. Parthasarathyand Sunder's result is recovered in a very simple way. In thecases of the Brownian motion or Poisson process interpretationof the Fock space, the result characterizes those random variablesthat are orthogonal to the exponential of any sum of n incrementsof the Brownian motion or Poisson process.     

过离散次数分布模型的尾部特征

在保险精算和生物统计等领域,离散型次数分布模型的应用十分广泛.当实际数据的尾部较长(即过离散),且零点的概率较大时,许多模型的拟合效果往往欠佳.本文通过计算概率之比的极限和偏度系数,对混合泊松分布和复合泊松分布的右尾特征和零点概率进行了比较,给出了它们的尾部排列顺序,以及尾部长短与零点概率的关系,从而为模型的构造或选择提供了一种指导.本文最后应用一组实际数据说明了在构造或选择次数分布模型时如何考虑尾部特征,从而改善对实际数据的拟合效果.     

Malliavin and Dirichlet structures for independent random variables

On any denumerable product of probability spaces, we construct a Malliavin gradient and then a divergence and a number operator. This yields a Dirichlet structure which can be shown to approach the usual structures for Poisson and Brownian processes. We obtain versions of almost all the classical functional inequalities in discrete settings which show that the Efron–Stein inequality can be interpreted as a Poincaré inequality or that the Hoeffding decomposition of $U$-statistics can be interpreted as an avatar of the Clark representation formula. Thanks to our framework, we obtain a bound for the distance between the distribution of any functional of independent variables and the Gaussian and Gamma distributions.     

Generalized Inv-Log-Gamma-G processes

Abstract

Gamma processes belong to subordinators for which very small jumps occurs infinitely many times in any finite time interval but their sums are finite. Here we consider their novel and important modifications with a nice application potential. A generalization of fractional kth lower record value process defined in Bieniek and Szynal, called Inverse-Log-Gamma-G process is investigated. Explicit relation with the Gamma process is presented and conditional, posterior and finite dimensional distributions are derived. The results are obtained by appropriate transformations of known stochastic processes. In contrast with the regression this allows us to describe the finite dimensional distributions of the processes of interest and in this way to make their full characterization.     

Determining <Emphasis Type="Italic">p</Emphasis>-values for systems cointegration tests with a prior adjustment for deterministic terms

Following Doornik (J Econ Surv 12:573–593, 1998) I present a procedure to approximate the asymptotic distributions of systems cointegration tests with a prior adjustment for deterministic terms suggested by Lütkepohl (Econometrica 72:647–662, 2004), Saikkonen and Lütkepohl (Econometric Theory 16:373–406, 2000a, J Business Econ Stat 18:451–464, 2000b, Time Series Anal 21:435–456, 2000c) and Saikkonen and Luukkonen (J Econ 81:93–126, 1997). These tests rely upon different assumptions as to the inclusion of deterministic components such as a constant, a linear trend or a level shift. The asymptotic distributions, which are functions of Brownian motions, are approximated by Gamma distributions. Only estimates of the mean and variance of the asymptotic test distributions are needed to fit the Gamma distributions. Such estimates are obtained from response surfaces. The required coefficients to compute the asymptotic moments are presented in this paper. Via the fitted Gamma distributions one can, then, easily derive p-values or arbitrary percentiles.     

Duration dependence models for claim counts

The aim of the paper is to introduce new claim count distributions constructed from different waiting time assumptions, such as the Exponential, Gamma and Weibull distributions. These models are then fitted to panel data with Gamma distributed random effects. The random effects allow for serial dependence and take residual heterogeneity into account. Predictive distributions are obtained with the help of Markov Chain Monte Carlo simulations. The approach is illustrated on the basis of a Belgian motor third party liability insurance portfolio observed for three years.     

Bilateral gamma distributions and processes in financial mathematics

We present a class of Lévy processes for modelling financial market fluctuations: bilateral Gamma processes. Our starting point is to explore the properties of bilateral Gamma distributions, and then we turn to their associated Lévy processes. We treat exponential Lévy stock models with an underlying bilateral Gamma process as well as term structure models driven by bilateral Gamma processes, and apply our results to a set of real financial data (DAX 1996–1998).     

On generalized binomial and multinomial distributions and their relation to generalized Poisson distributions

Summary The binomial and multinomial distributions are, probably, the best known distributions because of their vast number of applications. The present paper examines some generalizations of these distributions with many practical applications. Properties of these generalizations are studied and models giving rise to them are developed. Finally, their relationship to generalized Poisson distributions is examined and limiting cases are given.     

Limit theorems for the multivariate binomial distribution

Nonsingular limit distributions are determined for sequences of affine transformations of random vectors whose distributions are multivariate binomial. Each of these limit distributions is that of an affine transformation of a random vector having a multivariate normal distribution or a multivariate Possion distribution or a joint distribution of two independent random vectors, one normal and the other Poisson.     

第Ⅲ类非自共轭锥上的Gamma函数

本文将Ｇａｍｍａ函数及Ｓｉｅｇｅｌ积分推广到一般的第Ⅲ类非自共轭锥上,作为其应用,显式给出了以这些锥为底的管状域（也称第一类Ｓｉｅｇｅｌ域）的Ｃａｕｃｈｙ－Ｓｚｅｇｏ核和形式Ｐｏｉｓｓｏｎ核。关键词     

Simulation of correlated Poisson variables

Generating correlated Poisson random variables is fundamental in many applications in the management and engineering fields, and in many others where multivariate count data arise. Multivariate Poisson data are often approximately simulated by either independent univariate Poisson or multivariate Normal data, whose implementation is provided by the most common statistical software packages such as R . However, such simulated data are often not satisfactory. Alternatively, methods for simulating multivariate Poisson data can be used, but they are adversely affected by limitations ranging from computational complexity to restrictions on the correlation matrix, which dramatically reduce their practical applicability. In this work, we propose a new method that is highly accurate and computationally efficient and can be usefully employed even by non‐expert users in generating correlated Poisson data (and, more generally, any discrete variable), with assigned marginal distributions and correlation matrix. Copyright © 2014 John Wiley & Sons, Ltd.     

有限混合Gamma分布的拓扑稠密性证明

首先给出了有限混合Erlang分布在正实数轴上所有概率分布中稠密的理论证明,进而给出了混合Gamma分布具有稠密性的结论,说明有限混合Gamma分布具有广泛的适用性,可以用来刻画正实数轴上的任意随机变量.     

Testing Departures from Gamma, Rayleigh and Truncated Normal Distributions

This paper provides necessary and sufficient conditions for a solution to likelihood equations for an exponential family of distributions, which includes Gamma, Rayleigh and singly truncated normal distributions. Furthermore, the maximum likelihood estimator is obtained as a limit case when the equations have no solution. These results provide a way to test departures from Rayleigh and singly truncated normal distributions using the likelihood ratio test. A new easy way to test departures from a Gamma distribution is also introduced.     

First Exit Times for Ordinary and Compound Poisson Processes with Non-linear Boundaries

Distributions of the first-exit times from a region with concave upper boundary are discussed for ordinary and compound Poisson processes. Explicit formulae are developed for the case of ordinary Poisson processes. Recursive formulae are given for the compound Poisson case, where the jumps are positive, having discrete or continuous distributions with finite means. Applications to sequential point estimation and insurance are illustrated.      

第I类非自共轭锥上的Gamma函数

本文将Ｇａｍｍａ函数及Ｓｉｅｇｅｌ积分推广到一般的第Ｉ类非自共轭锥上．作为其应用，显式给出了以这些锥为底的管状域（或第一类Ｓｉｅｇｅｌ域）的Ｃａｕｃｈｙ Ｓｚｅｇ¨ｏ核和形式Ｐｏｉｓｏｎ核．     

EXPLICIT EXPRESSIONS FOR SOME DISTRIBUTIONS RELATED TO RUIN PROBLEMS

The classical risk process that is perturbed by diffusion is studied .The explicit expressions for the runi probability and the surplus distribution of the risk process at the time of runi are obtained when the claim amount distribution is a finite mixture of exponential distributions of a Gamma (2,α） distribution.