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Periodica Mathematica Hungarica
Article . 1988 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
zbMATH Open
Article . 1988
Data sources: zbMATH Open
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Kernel approximations of a wiener process

Kernel approximations of a Wiener process
Authors: Stadtmüller, U.;

Kernel approximations of a wiener process

Abstract

Consider a standard Wiener process W(.) on the real line and a kernel approximation of this process. The purpose of this paper is to study the deviation of these two processes, i.e. \[ X_ h(x)=h^{-1}\int K((v- x)/h)W(v)dv-W(x),\quad as\quad h\to 0+. \] Local and global weak and strong limit theorems for \(X_ h(.)\), \(h\to 0+\), are given, e.g. it is proven that for a certain class of kernels \[ \lim _{h\to 0+}\sup _{0\leq x\leq 1}X_ h(x)(2h \log h^{-1})^{-}=c\quad a.s. \] where \(c=c(K)\) is an explicit constant. Processes which correspond to \(X_ h\) occur in the asymptotics of nonparametric curve estimates.

Related Organizations
Keywords

asymptotics of nonparametric curve estimates, kernel approximation, Approximation by operators (in particular, by integral operators), Gaussian processes, Rate of convergence, degree of approximation, Brownian motion, weak and strong limit theorems

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Average
Top 10%
Average
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