scholarly journals Monotone and boolean convolutions for non-compactly supported probability measures

2009 ◽  
Vol 58 (3) ◽  
pp. 1151-1186 ◽  
Author(s):  
Uwe Franz
Keyword(s):  
Probability Measures ◽  
Compactly Supported

scholarly journals Cauchy–Stieltjes families with polynomial variance functions and generalized orthogonality

2019 ◽  
Vol 39 (2) ◽  
pp. 237-258 ◽  
Author(s):  
Włodzimierz Bryc ◽  
Raouf Fakhfakh ◽  
Wojciech Młotkowski
Keyword(s):  
Free Probability ◽  
Probability Measures ◽  
Arbitrary Degree ◽  
Classical Probability ◽  
Compactly Supported ◽  
Variance Functions ◽  
Additional Variance

This paper studies variance functions of Cauchy–Stieltjes Kernel CSK families generated by compactly supported centered probability measures. We describe several operations that allow us to construct additional variance functions from known ones. We construct a class of examples which exhausts all cubic variance functions, and provide examples of polynomial variance functions of arbitrary degree. We also relate CSK families with polynomial variance functions to generalized orthogonality.Our main results are stated solely in terms of classical probability; some proofs rely on analytic machinery of free probability.

scholarly journals Positive Definite and Related Functions on Hypergroups

1991 ◽  
Vol 43 (2) ◽  
pp. 242-254 ◽  
Author(s):  
Walter R. Bloom ◽  
Paul Ressel
Keyword(s):  
Positive Definite ◽  
Probability Measures ◽  
Representation Theorems ◽  
Compactly Supported ◽  
Completely Monotone ◽  
Considerable Simplification ◽  
Commutative Hypergroup ◽  
Completely Alternating

AbstractIn this paper we make use of semigroup methods on the space of compactly supported probability measures to obtain a complete Lévy-Khinchin representation for negative definite functions on a commutative hypergroup. In addition we obtain representation theorems for completely monotone and completely alternating functions. The techniques employed here also lead to considerable simplification of the proofs of known results on positive definite and negative definite functions on hypergroups.

LIFTING THE FUNCTOR ITO THE CATEGORY OF UNIFORM SPACES

2020 ◽  
Vol 4 (1) ◽  
pp. 29-39
Author(s):  
Dilrabo Eshkobilova ◽  
Keyword(s):  
Compact Support ◽  
Probability Measures ◽  
Uniform Spaces ◽  
Continuous Maps ◽  
Uniformly Continuous

Uniform properties of the functor Iof idempotent probability measures with compact support are studied. It is proved that this functor can be lifted to the category Unif of uniform spaces and uniformly continuous maps

Generic rotation sets

2020 ◽  
pp. 1-13
Author(s):  
SEBASTIÁN PAVEZ-MOLINA
Keyword(s):  
Dynamical System ◽  
Convex Body ◽  
Probability Measures ◽  
Topological Dynamical System ◽  
Continuous Vector ◽  
Rotation Set ◽  
Vector Valued Function ◽  
Vector Valued ◽  
Uniquely Ergodic ◽  
Dense Set

Abstract Let $(X,T)$ be a topological dynamical system. Given a continuous vector-valued function $F \in C(X, \mathbb {R}^{d})$ called a potential, we define its rotation set $R(F)$ as the set of integrals of F with respect to all T-invariant probability measures, which is a convex body of $\mathbb {R}^{d}$ . In this paper we study the geometry of rotation sets. We prove that if T is a non-uniquely ergodic topological dynamical system with a dense set of periodic measures, then the map $R(\cdot )$ is open with respect to the uniform topologies. As a consequence, we obtain that the rotation set of a generic potential is strictly convex and has $C^{1}$ boundary. Furthermore, we prove that the map $R(\cdot )$ is surjective, extending a result of Kucherenko and Wolf.

scholarly journals On a Variational Definition for the Jensen-Shannon Symmetrization of Distances Based on the Information Radius

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 464
Author(s):  
Frank Nielsen
Keyword(s):  
Diversity Index ◽  
Diversity Indices ◽  
Shannon Diversity Index ◽  
Probability Measures ◽  
Variational Optimization ◽  
Shannon Diversity ◽  
Concept Of Information ◽  
Jensen Shannon Divergence

We generalize the Jensen-Shannon divergence and the Jensen-Shannon diversity index by considering a variational definition with respect to a generic mean, thereby extending the notion of Sibson’s information radius. The variational definition applies to any arbitrary distance and yields a new way to define a Jensen-Shannon symmetrization of distances. When the variational optimization is further constrained to belong to prescribed families of probability measures, we get relative Jensen-Shannon divergences and their equivalent Jensen-Shannon symmetrizations of distances that generalize the concept of information projections. Finally, we touch upon applications of these variational Jensen-Shannon divergences and diversity indices to clustering and quantization tasks of probability measures, including statistical mixtures.

scholarly journals Discussion on Competition for Spatial Statistics for Large Datasets

2021 ◽  
Author(s):  
Roman Flury ◽  
Reinhard Furrer
Keyword(s):  
Spatial Statistics ◽  
Covariance Function ◽  
Likelihood Function ◽  
Large Datasets ◽  
Missing Observations ◽  
Covariance Model ◽  
Compactly Supported ◽  
Covariance Tapering ◽  
Simple Kriging ◽  
Estimated Parameters

AbstractWe discuss the experiences and results of the AppStatUZH team’s participation in the comprehensive and unbiased comparison of different spatial approximations conducted in the Competition for Spatial Statistics for Large Datasets. In each of the different sub-competitions, we estimated parameters of the covariance model based on a likelihood function and predicted missing observations with simple kriging. We approximated the covariance model either with covariance tapering or a compactly supported Wendland covariance function.

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