A remark on Slutsky's theorem
A Riemann approach to random variation
This essay outlines a generalized Riemann approach to the analysis of random variation and illustrates it by a construction of Brownian motion in a new and simple manner.
A solution of an equation for indexed functions
A system of random nonlinear variational inclusions involving random fuzzy mappings and -monotone set-valued mappings.
A version of the strong law of large numbers universal under mappings
About the density of spectral measure of the two-dimensional SaS random vector
In this paper, we consider a symmetric α-stable p-sub-stable two-dimensional random vector. Our purpose is to show when the function is a characteristic function of such a vector for some p and α. The solution of this problem we can find in [3], in the language of isometric embeddings of Banach spaces. Our proof is based on simple properties of stable distributions and some characterization given in [4].
Algorithmical Definition of Finite Markov Sequence
Alternative definitions of conditional possibilistic measures
The aim of this paper is to survey and discuss, very briefly, some ways how to introduce, within the framework of possibilistic measures, a notion analogous to that of conditional probability measure in probability theory. The adjective “analogous” in the last sentence is to mean that the conditional possibilistic measures should play the role of a mathematical tool to actualize one’s degrees of beliefs expressed by an a priori possibilistic measure, having obtained some further information concerning...
An addendum to a remark on Slutsky's theorem
An Alpern tower independent of a given partition
Given a measure-preserving transformation T of a probability space (X,ℬ,μ) and a finite measurable partition ℙ of X, we show how to construct an Alpern tower of any height whose base is independent of the partition ℙ. That is, given N ∈ ℕ, there exists a Rokhlin tower of height N, with base B and error set E, such that B is independent of ℙ, and TE ⊂ B.
An analysis of the Rüschendorf transform - with a view towards Sklar’s Theorem
We revisit Sklar’s Theorem and give another proof, primarily based on the use of right quantile functions. To this end we slightly generalise the distributional transform approach of Rüschendorf and facilitate some new results including a rigorous characterisation of an almost surely existing “left-invertibility” of distribution functions.
An application of a functional equation to information theory
An axiomatization of extensional probability measures
An extended problem to Bertrand's paradox
Bertrand's paradox is a longstanding problem within the classical interpretation of probability theory. The solutions 1/2, 1/3, and 1/4 were proposed using three different approaches to model the problem. In this article, an extended problem, of which Bertrand's paradox is a special case, is proposed and solved. For the special case, it is shown that the corresponding solution is 1/3. Moreover, the reasons of inconsistency are discussed and a proper modeling approach is determined by careful examination...
An extension of a Meyer's theorem
An extension of the probability logic
An individual ergodic theorem for random fuzzy sets.
An integral representation of randomized probabilities and its applications
Analysis on some linear sets
The note discusses a probabilistic method for constructing “small” sets, with regard to differentiable transformations and to quantitative measures of independence.
Aplicación de las submedidas C a las probabilidades comparativas.
Introducimos en este trabajo el concepto de submedida C (comparativa), sobre un álgebra de conjuntos D, estudiamos propiedades de estas submedidas que serán necesarias para la cuantificación de probabilidades comparativas (P.C.) y se relacionan con otro concepto introducido recientemente por Dobrakov, que es el de submedida I. Se estudian las condiciones bajo las que la convergencia de una sucesión (An) en D subordina la convergencia de (An, ≥) y la representación cuantitativa de P.C. mediante submedidas...