scholarly journals Theory of Probabilistic Connectedness

2020 ◽  
Author(s):  
Yu-Lin Chou

We introduce and study a notion of probabilistic connectedness, which we term $proconnectedness$, defined in terms of partitions of a probability space into two nonempty disjoint independent events. Both proconnectedness and disproconnectedness are shown to be invariants (in a suitable sense) under isomorphic random elements. We show that a substantial part of the fundamental theory of topological connectedness admits a natural counterpart in the present theory of proconnectedness. Some applications and connections regarding limit theorems, cardinality equality of measurability structures, atomic distributions, and singular distributions are discussed.

1976 ◽  
Vol 28 (2) ◽  
pp. 403-407
Author(s):  
A. G. Mucci

Let be an adapted sequence of integrable random variables on the probability space . Let us set .The following result can be immediately derived from Brown [2]:


2021 ◽  
Vol 6 (11) ◽  
pp. 12166-12181
Author(s):  
Shuyan Li ◽  
◽  
Qunying Wu

<abstract><p>Limit theorems of sub-linear expectations are challenging field that has attracted widespread attention in recent years. In this paper, we establish some results on complete integration convergence for weighted sums of arrays of rowwise extended negatively dependent random variables under sub-linear expectations. Our results generalize the complete moment convergence of the probability space to the sub-linear expectation space.</p></abstract>


1991 ◽  
Vol 28 (04) ◽  
pp. 751-761 ◽  
Author(s):  
A. Kwieciński ◽  
R. Szekli

Sufficient conditions are given under which two simple point processes on the positive half-line can be stochastically compared as random elements of D(0,∞) or R∞ + Using a martingale approach to point processes, the conditions are proposed via a compensator function family. Appropriate versions of the processes being compared are constructed on the same probability space. The results are illustrated by replacement policies and semi-Markov point processes.


2003 ◽  
Vol 03 (04) ◽  
pp. 477-497 ◽  
Author(s):  
NADINE GUILLOTIN-PLANTARD ◽  
DOMINIQUE SCHNEIDER

Let [Formula: see text] be a dynamical system where [Formula: see text] is a probability space and T an invertible transformation preserving the measure μ. Let (Sk)k≥0 be a transient ℤ-random walk. Let f ∈ L2(μ) and H ∈ ]0,1[, we study the convergence in distribution of the sequence [Formula: see text] We also study the case when the random walk (Sk)k≥0 is replaced by an increasing deterministic subsequence of integers.


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