Generalized convolution product of an infinitely divisible distribution and a Bernoulli distribution

2021 ◽  
pp. 1-8
Author(s):  
Ben Salah Nahla
Keyword(s):  
Divisible Distribution ◽  
Convolution Product ◽  
Bernoulli Distribution ◽  
Infinitely Divisible Distribution ◽  
Generalized Convolution ◽  
Infinitely Divisible

scholarly journals On the Infinitely Divisible of Meixner Distribution

2018 ◽  
Vol 3 (4) ◽  
pp. 147
Author(s):  
Dodi Devianto ◽  
Jayanti Herli ◽  
Maiyastri Maiyastri ◽  
Rahma Diana Safitri
Keyword(s):  
Characteristic Function ◽  
Lévy Process ◽  
Goodness Of Fit ◽  
Divisible Distribution ◽  
Levy Process ◽  
Financial Data ◽  
Infinitely Divisible Distribution ◽  
Goodness Of Fit Test ◽  
Infinitely Divisible

The log-returns of most financial data show a significant leptokurtosis. For the better fit we showed a special levy process which is called the Meixner process. The Meixner distribution belongs to the class of infinitely divisible distribution chracterized by using characteristic function and it was proposed as a model for represented efficiently of the log-returns of financial data. The perfect fit of underlying Meixner distribution performing by using goodness of fit test.

scholarly journals The effect of random scale changes on limits of infinitesimal systems

1978 ◽  
Vol 1 (3) ◽  
pp. 339-372
Author(s):  
Patrick L. Brockett
Keyword(s):  
Sufficient Conditions ◽  
Random Variables ◽  
Domain Of Attraction ◽  
Divisible Distribution ◽  
Infinitely Divisible Distribution ◽  
Infinitely Divisible ◽  
Stable Law ◽  
Scale Parameters ◽  
Exact Relationship ◽  
Random Scale

SupposeS={{Xnj,   j=1,2,…,kn}}is an infinitesimal system of random variables whose centered sums converge in law to a (necessarily infinitely divisible) distribution with Levy representation determined by the triple(γ,σ2,M). If{Yj,   j=1,2,…}are independent indentically distributed random variables independent ofS, then the systemS′={{YjXnj,j=1,2,…,kn}}is obtained by randomizing the scale parameters inSaccording to the distribution ofY1. We give sufficient conditions on the distribution ofYin terms of an index of convergence ofS, to insure that centered sums fromS′be convergent. If such sums converge to a distribution determined by(γ′,(σ′)2,Λ), then the exact relationship between(γ,σ2,M)and(γ′,(σ′)2,Λ)is established. Also investigated is when limit distributions fromSandS′are of the same type, and conditions insuring products of random variables belong to the domain of attraction of a stable law.

Max-infinite divisibility and multivariate total positivity

1994 ◽  
Vol 31 (3) ◽  
pp. 721-730 ◽  
Author(s):  
Abdulhamid A. Alzaid ◽  
Frank Proschan
Keyword(s):  
Distribution Function ◽  
Total Positivity ◽  
Positive Function ◽  
Infinite Divisibility ◽  
Divisible Distribution ◽  
Infinitely Divisible Distribution ◽  
Infinitely Divisible ◽  
Positive Dependence ◽  
Totally Positive

The concept of max-infinite divisibility is viewed as a positive dependence concept. It is shown that every max-infinitely divisible distribution function is a multivariate totally positive function of order 2 (MTP2). Inequalities are derived, with emphasis on exchangeable distributions. Applications and examples are given throughout the paper.

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