Results 161 to 170 of about 322 (196)

Infinitely divisible distributions in turbulence

Physical Review E, 1994
The imbedding of the scale similarity of random fields into the theory of infinitely divisible probability distributions is considered. The general probability distribution for the breakdown coefficients of turbulent energy dissipation is obtained along with corresponding similarity exponents.
openaire   +2 more sources

Convolution equivalence and infinite divisibility

Journal of Applied Probability, 2004
Known results relating the tail behaviour of a compound Poisson distribution function to that of its Lévy measure when one of them is convolution equivalent are extended to general infinitely divisible distributions. A tail equivalence result is obtained for random sum distributions in which the summands have a two-sided distribution.
openaire   +2 more sources

Max-infinite divisibility

Journal of Applied Probability, 1977
Necessary and sufficient conditions are given for a distribution function in ℝ2 to be max-infinitely divisible. The d.f. F is max i.d. if F t is a d.f. for every t > 0. This property is essential in defining multivariate extremal processes and arises in an approach to the study of the range of an i.i.d. sample.
Balkema, A. A., Resnick, S. I.
openaire   +2 more sources

On Infinite Divisibility of Convolution and Mapping Kernels

Fundamenta Informaticae, 2017
Determining whether convolution and mapping kernels are always infinitely divisible has been an unsolved problem. The mapping kernel is an important class of kernels and is a generalization of the well-known convolution kernel. The mapping kernel has a wide range of application. In fact, most of kernels known in the literature for discrete data such as
openaire   +2 more sources

Infinitely Divisible Distributions

1975
A distribution function F (x) and the corresponding c.f. f (t) are said to be infinitely divisible if for every positive integer n there exists a c.f. f n (t) such that $$f\left( t \right) = {\left( {{f_n}\left( t \right)} \right)^n}$$ (1.1)
openaire   +1 more source

Infinitely Divisible Processes

2014
In Chapter 11 we investigate infinitely divisible processes in a far more general setting than what mainstream probability theory has yet considered: we make no assumption of stationarity of increments of any kind and our processes are actually indexed by an abstract set.
openaire   +1 more source

Infinitely Divisible Processes

Theory of Probability & Its Applications, 1970
openaire   +2 more sources

On Infinitely Divisible Distributions

Theory of Probability & Its Applications, 1975
openaire   +2 more sources

Infinite Divisibility of GCD Matrices

The American Mathematical Monthly, 2008
Rajendra Bhatia, J. A. Dias da Silva
openaire   +2 more sources

Infinite Divisibility

2009
Bjørn Sundt, Raluca Vernic
openaire   +1 more source