Results 91 to 100 of about 166,082,168 (134)
工程科学与技术Significance Rainfall-induced clustered landslides are among the most destructive regional geohazards in the mountainous areas of southeastern China.
HUANG Yu +11 more
doaj
Weak convergence in applied probability
Weak convergence of probability measures on function spaces has been active area of research in recent years. While the theory has a somewhat abstract base, it is extremely useful in a wide variety of problems and we believe has much to offer to applied ...
Iglehart, Donald L.
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Weak Convergence of Probability Measures on Metric Spaces of Nonlinear Operators [PDF]
Bulletin of the Institute of Mathematics Academia Sinica NEW SERIES, 2016 openaire +1 more source
The weak convergence of uniform measures
This paper presents a necessary and sufficient condition for the weak convergence of uniform measures on an arbitrary Hausdorff uniform space in terms of their projections in metric spaces. This result was inspired by and extends a result of Bartoszynski
Caby, Errol
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A note on the weak convergence of probability measures in the D[0,1] space
Let [tau] be a regular metric as defined below for the D=D[0,1] space. Even when (D,[tau]) is not a separable and complete metric space we show (i) that the usual conditions on a sequence of probability measures in (D,[tau]) ensures its weak convergence ...
Pakshirajan, R.P.
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Weak Convergence of Probability Measures on the Function Space $C\lbrack 0, \infty)$
The Annals of Mathematical Statistics, 1970 openaire +3 more sources
An application of transformation of drift to weak convergence of quasimartingale probability measuresopenaire +1 more source
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On the Weak Convergence of Probability Measures in Orlicz Spaces
Theory of Probability and Its Applications, 1996Necessary and sufficient conditions for weak convergence of probability measures in separable Orlicz spaces in terms of characteristic functionals and norm moments are given.
exaly +3 more sources
Almost sure weak convergence of random probability measures
Stochastics, 2006Given a sequence (μ n ) of random probability measures on a metric space S, consider the conditions: (i) μ n →μ (weakly) a.s. for some random probability measure μ on S; (ii) μ n (f) converges a.s. for all f∈C b (S). Then, (i) implies (ii), while the converse is not true, even if S is separable. For (i) and (ii) to be equivalent, it is enough that S is
Patrizia Berti +2 more
exaly +4 more sources
On weak convergence of probability measures, channel capacity and code error probabilities
IEEE Transactions on Information Theory, 1996Let \({\mathcal X}\) be the possibly infinite set of channel inputs and \({\mathcal Y}\) the output alphabet where \({\mathcal Y}\) is the Borel \(\sigma\)-field of a separable metric space \(({\mathcal Y},d)\). A channel \({\mathcal C}\) is a family of probability measures on \({\mathcal Y}\), i.e., \({\mathcal C}=(P^x)_{x\in{\mathcal X}}\) where \(P ...
exaly +2 more sources