scholarly journals The Infinitely Divisible Characteristic Function of Compound Poisson Distribution as the Sum of Variational Cauchy Distribution

2019 ◽  
Vol 1397 ◽  
pp. 012065
Author(s):  
D Devianto ◽  
Sarah ◽  
H Yozza ◽  
F Yanuar ◽  
Maiyastri
Keyword(s):  
Characteristic Function ◽  
Poisson Distribution ◽  
Cauchy Distribution ◽  
Compound Poisson Distribution ◽  
Infinitely Divisible ◽  
Compound Poisson

scholarly journals Multivariate Compound Poisson Distributions and Infinite Divisibility

2000 ◽  
Vol 30 (2) ◽  
pp. 305-308 ◽  
Author(s):  
Bjørn Sundt
Keyword(s):  
Poisson Distribution ◽  
Infinite Divisibility ◽  
Compound Poisson Distribution ◽  
Infinitely Divisible ◽  
Compound Poisson ◽  
Multivariate Extension ◽  
Poisson Distributions ◽  
Univariate Distribution

AbstractIn this note we give a multivariate extension of the proof of Ospina & Gerber (1987) of the result of Feller (1968) that a univariate distribution on the non-negative integers is infinitely divisible if and only if it can be expressed as a compound Poisson distribution.

Log-Compound-Poisson Distribution Model of Intermittency in Turbulence

1998 ◽  
Vol 53 (10-11) ◽  
pp. 828-832
Author(s):  
Feng Quing-Zeng
Keyword(s):  
Energy Dissipation ◽  
Poisson Distribution ◽  
Turbulent Energy ◽  
Compound Poisson Distribution ◽  
Distribution Model ◽  
Velocity Difference ◽  
Scaling Exponents ◽  
Compound Poisson ◽  
Developed Turbulence ◽  
Experimental Values

Abstract The log-compound-Poisson distribution for the breakdown coefficients of turbulent energy dissipation is proposed, and the scaling exponents for the velocity difference moments in fully developed turbulence are obtained, which agree well with experimental values up to measurable orders. The under-lying physics of this model is directly related to the burst phenomenon in turbulence, and a detailed discussion is given in the last section.

On a stochastic process occurring in queueing systems

1965 ◽  
Vol 2 (2) ◽  
pp. 467-469 ◽  
Author(s):  
U. N. Bhat
Keyword(s):  
Stochastic Process ◽  
Poisson Distribution ◽  
Waiting Time ◽  
Queueing Systems ◽  
Distribution Functions ◽  
Compound Poisson Distribution ◽  
Compound Poisson ◽  
Transition Distribution

SummaryTransition distribution functions (d.f.) of the stochastic process u + t − X(t), where X(t) has a compound Poisson distribution, are used to derive explicit results for the transition d.f.s of the waiting time processes in the queueing systems M/G/1 and GI/M/1.

Poisson theorem for non-homogeneous Markov chains

1989 ◽  
Vol 26 (03) ◽  
pp. 637-642 ◽  
Author(s):  
Janusz Pawłowski
Keyword(s):  
Markov Chains ◽  
Poisson Distribution ◽  
Sufficient Conditions ◽  
Necessary And Sufficient Conditions ◽  
Compound Poisson Distribution ◽  
Convergence In Distribution ◽  
Compound Poisson ◽  
Necessary And Sufficient

This paper gives necessary and sufficient conditions for the convergence in distribution of sums of the 0–1 Markov chains to a compound Poisson distribution.

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