Results 271 to 280 of about 12,541,553 (294)

Bootstrap Approximation of Distributions of the L-Statistics

Journal of Mathematical Sciences, 2002
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Moderate Deviations for a Class of L-Statistics

Acta Applicandae Mathematicae, 2008
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L-statistic combined with compressive sensing

SPIE Proceedings, 2013
Robust signal analysis based on the L-statistic was introduced for signals disturbed with high additive impulse noise. The basic idea is that a certain, usually large number of arbitrary positioned signal samples is declared as heavily corrupted by noise. Then, these samples are removed. Thus, they can be considered as absent or unavailable.
Srdjan Stankovic, Ljubisa Stankovic, Irena Orovic   +2 more
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Large and moderate deviations for L-statistics

Lithuanian Mathematical Journal, 1992
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Large deviations for L-statistics

Statistics & Decisions, 2007
The purpose of this paper is to establish a functional large deviations principle (LDP) for L-statistics under some new tail conditions. The method is based on Sanov's theorem and on basic tools of large deviations theory. Our study includes a full treatment of the case of the uniform law and an example in which the rate function can be calculated very
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Probabilities of large deviations for L-statistics

Lithuanian Mathematical Journal, 1991
See the review in Zbl 0706.62015.
Bentkus, V., Zitikis, R.
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A note on adaptive l-statistics

Communications in Statistics - Theory and Methods, 1982
The purpose of this note is to give a simple demonstration of the apparently widely-known principle that, under suitable conditions (primarily of a symmetry nature) an adaptive L-sta-tistic has the same asymptotic distribution as a non-adaptive L-statistic.
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Bootstrapping for generalized l-statistics

Communications in Statistics - Theory and Methods, 1989
Serfling (1984) introduced a class of generalized L-statistics containing many different types of statistics. For a generalized L-statistic Tn, we establish a bootstrap representation for the bootstrap statistic —Tn, which shows that —Tn can be approximated by the difference between a U-statistic and its bootstrap analog.
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Probability Inequalities and Limit Theorems for Generalized L-Statistics

Lithuanian Mathematical Journal, 2003
This paper extends the authors' previous work [Sib. Mat. J. 42, 217--231 (2001); translation from Sib. Mat. Zh. 42, 258--274 (2001; Zbl 0986.60014). Exponential bounds are obtained for the tails of the distributions of generalized \(L\)-statistics based on a sample from an exponential distribution.
Baklanov, E. A., Borisov, I. S.
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A Glivenko-Cantelli Theorem and Strong Laws for L-Statistics

Journal of Theoretical Probability, 1998
Consider the Marcinkiewicz-Zygmund strong law (MZSLLN) which states the almost sure convergence of \(n^{-1}\sum^n_{i=1} X_i=c+o (n^{(1-p)/p})\) a.s. as \(n\to\infty\), for \(\{X_i, i\geq 1\}\) i.i.d.
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