In this paper we review analogues of narrow ( = weak) convergence of probability measures on a metric space, and present a synthesis that incorporates all separate cases and seems to be the right framework for the "large deviation principle".weak convergence narrow convergence vague convergence hypo convergence portmanteau theorem large deviation principle capacities random closed sets random semicontinuous functions
Several notions of convergence for subsets of metric spaces appear in the literature. In this paper...
Abstract. It it shown that Kolmogorov’s Extension Theorem can be applied in the following nonstandar...
ABSTRACT. Fatou's lemmas and Lebesgue's convergence theorems are established for multi val...
This book provides a thorough exposition of the main concepts and results related to various types o...
none3noGiven a sequence (mn) of random probability measures on a metric space S, consider the condit...
Abstract. The hypo-convergence of upper semicontinuous functions provides a natural framework for th...
The hypo-convergence of upper semicontinuous functions provides a natural framework for the study of...
In this thesis we define two most common types of convergence of probability measures and show relat...
Given a sequence (mn) of random probability measures on a metric space S, consider the conditions: ...
Given a sequence (mn) of random probability measures on a metric space S, consider the conditions: ...
Herein, we generalize and extend some standard results on the separation and convergence of probabil...
AbstractHerein, we generalize and extend some standard results on the separation and convergence of ...
We address the missing analog of vague convergence in the weak-converge-large-deviations analogy. Sp...
A large number of results are available about the weak convergence of probability measures in spaces...
Weak convergence of probability measures on function spaces has been active area of research in rece...
Several notions of convergence for subsets of metric spaces appear in the literature. In this paper...
Abstract. It it shown that Kolmogorov’s Extension Theorem can be applied in the following nonstandar...
ABSTRACT. Fatou's lemmas and Lebesgue's convergence theorems are established for multi val...
This book provides a thorough exposition of the main concepts and results related to various types o...
none3noGiven a sequence (mn) of random probability measures on a metric space S, consider the condit...
Abstract. The hypo-convergence of upper semicontinuous functions provides a natural framework for th...
The hypo-convergence of upper semicontinuous functions provides a natural framework for the study of...
In this thesis we define two most common types of convergence of probability measures and show relat...
Given a sequence (mn) of random probability measures on a metric space S, consider the conditions: ...
Given a sequence (mn) of random probability measures on a metric space S, consider the conditions: ...
Herein, we generalize and extend some standard results on the separation and convergence of probabil...
AbstractHerein, we generalize and extend some standard results on the separation and convergence of ...
We address the missing analog of vague convergence in the weak-converge-large-deviations analogy. Sp...
A large number of results are available about the weak convergence of probability measures in spaces...
Weak convergence of probability measures on function spaces has been active area of research in rece...
Several notions of convergence for subsets of metric spaces appear in the literature. In this paper...
Abstract. It it shown that Kolmogorov’s Extension Theorem can be applied in the following nonstandar...
ABSTRACT. Fatou's lemmas and Lebesgue's convergence theorems are established for multi val...