AbstractOperator-stable laws and operator-semistable laws (introduced as limit distributions by M. Sharpe and R. Jajte, respectively) are characterized by decomposability properties. Disintegration of their corresponding Lévy measures requires appropriate cross sections. Furthermore in both situations the Lévy measures constitute a Bauer simplex whose extreme boundary can be explicitly given. Finally the infinitely differentiable Lebesgue density of an operator-semistable law is shown to be even analytic in some cases
AbstractLet μ be an infinitely divisible measure on a finite dimensional vector space. The problem o...
AbstractSubclasses L0 ⊃ L1 ⊃ … ⊃ L∞ of the class L0 of self-decomposable probability measures on a B...
Strictly operator-stable distributions are defined and discussed. Characterization of strictly stabl...
AbstractOperator-stable laws and operator-semistable laws (introduced as limit distributions by M. S...
AbstractIn this paper we define semi-stable probability measures (laws) on a real separable Hilbert ...
"By definition any stable distribution is semistable. For the converse relation we will show that ce...
AbstractStrictly operator-stable distributions are defined and discussed. Characterization of strict...
AbstractThe problem of the characterization of multivariate distribution through the property of the...
AbstractSharpe investigated the structure of full operator-stable measures μ on a vector group V and...
AbstractIt is shown that every genuinely d-dimensional operator-self-decomposable distribution is ab...
AbstractIn 1937, Paul Lévy proved two theorems that characterize one-dimensional distribution functi...
AbstractSharpe has shown that full operator-stable distributions μ on Rn are infinitely divisible an...
AbstractA description of the class of semistable measures on a real separable Hilbert space is given
Abstract. The most prominent examples of (operator-) selfdecompos-able laws on vector spaces are (op...
AbstractIt is shown that every full eA decomposable probability measure on Rk, where A is a linear o...
AbstractLet μ be an infinitely divisible measure on a finite dimensional vector space. The problem o...
AbstractSubclasses L0 ⊃ L1 ⊃ … ⊃ L∞ of the class L0 of self-decomposable probability measures on a B...
Strictly operator-stable distributions are defined and discussed. Characterization of strictly stabl...
AbstractOperator-stable laws and operator-semistable laws (introduced as limit distributions by M. S...
AbstractIn this paper we define semi-stable probability measures (laws) on a real separable Hilbert ...
"By definition any stable distribution is semistable. For the converse relation we will show that ce...
AbstractStrictly operator-stable distributions are defined and discussed. Characterization of strict...
AbstractThe problem of the characterization of multivariate distribution through the property of the...
AbstractSharpe investigated the structure of full operator-stable measures μ on a vector group V and...
AbstractIt is shown that every genuinely d-dimensional operator-self-decomposable distribution is ab...
AbstractIn 1937, Paul Lévy proved two theorems that characterize one-dimensional distribution functi...
AbstractSharpe has shown that full operator-stable distributions μ on Rn are infinitely divisible an...
AbstractA description of the class of semistable measures on a real separable Hilbert space is given
Abstract. The most prominent examples of (operator-) selfdecompos-able laws on vector spaces are (op...
AbstractIt is shown that every full eA decomposable probability measure on Rk, where A is a linear o...
AbstractLet μ be an infinitely divisible measure on a finite dimensional vector space. The problem o...
AbstractSubclasses L0 ⊃ L1 ⊃ … ⊃ L∞ of the class L0 of self-decomposable probability measures on a B...
Strictly operator-stable distributions are defined and discussed. Characterization of strictly stabl...