Zobrazeno 1 - 10 of 36 pro vyhledávání: '"W. R. van Zwet"'
1
Miscellanea - The Times of Yuri Vasilyevich Prokhorov
Autor: Friedrich Götze, W. R. van Zwet
Publikováno v: Theory of Probability & Its Applications. 57:306-322
Yuri Vasilyevich Prokhorov is the eminence grise of Russian probability theory. Every one of us interested in probability or asymptotic statistics has come across his celebrated weak compactness theorem at one time or another. He was interviewed earl
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4e3fc2bd16bb92f27693a15e69488dfe
https://doi.org/10.1137/s0040585x97985972
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3
Asymptotic Efficiency of Inverse Estimators
Autor: A.C.M. van Rooij, Frits H. Ruymgaart, W. R. van Zwet
Publikováno v: Theory of Probability & Its Applications. 44:722-738
Inverse estimation concerns the recovery of an unknown input signal from blurred observations on a known transformation of that signal. The estimators considered in this paper are based on a regularized inverse of the transformation involved, employi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::73deab7679a1a99cb772b9c78d04cb69
https://doi.org/10.1137/s0040585x97977914
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4
Selected Works of Willem van Zwet
Autor: S. A. van de Geer, W. R. van Zwet, Marten Wegkamp
Publikováno v: Selected Works of Willem van Zwet
Three Fundamental Statistics Papers.- Asymptotic Statistics.- Second Order Asymptotics.- Resampling.- Applications.- Probabililty.
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::524ad0787ae2b0db77b20afb36a5e89a
https://doi.org/10.1007/978-1-4614-1314-1
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5
Asymptotic Expansions for the Power of Distributionfree Tests in the Two-Sample Problem
Autor: Peter J. Bickel, W. R. van Zwet
Publikováno v: Selected Works of Willem van Zwet ISBN: 9781461413134
Asymptotic expansions are established for the power of distributionfree tests in the two-sample problem. These expansions are then used to obtain deficiencies in the sense of Hodges and Lehmann for distributionfree tests with respect to their paramet
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https://doi.org/10.1007/978-1-4614-1314-1_11
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6
Van De Hulst on Robust Statistics: A Historical Note
Autor: W. R. van Zwet
Publikováno v: Selected Works of Willem van Zwet ISBN: 9781461413134
This paper provides a discussion of an unpuplished set of notes written in 1942 by the Dutch astronomer H.C. Van DE HULST. In these notes VAN DE HULST derives the asymptotic variances of M-estimators as well as trimed means and concludes that the asy
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::14f79aa9b58d5190a2de7a072217c7ca
https://doi.org/10.1007/978-1-4614-1314-1_3
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7
The Edgeworth Expansion for U-Statistics of Degree Two
Autor: Peter J. Bickel, Friedrich Götze, W. R. van Zwet
Publikováno v: Selected Works of Willem van Zwet ISBN: 9781461413134
An Edgeworth expansion with remainder o(N−1) is established for a U-statistic with a kernel h of degree 2. The assumptions involved appear to be very mild; in particular, the common distribution of the summands h(X i , X j ) is not assumed to be sm
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4a94ad5129344f437e1cd17fb286457d
https://doi.org/10.1007/978-1-4614-1314-1_14
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8
A Remark on Consistent Estimation
Autor: W. R. van Zwet, E. W. van Zwet
Publikováno v: Selected Works of Willem van Zwet ISBN: 9781461413134
In this paper we re-examine two auxiliary results in Putter and va.n Zwet [7]. Viewed in a new light these results provide some insight in two related phenomena, to wit consistency of estimators and local asymptotic equivariance. Though technically q
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8bda75fbd19dcb7cece11ee95600c657
https://doi.org/10.1007/978-1-4614-1314-1_9
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9
Resampling Fewer Than n Observations: Gains, Losses, and Remedies for Losses
Autor: W. R. van Zwet, Friedrich Götze, Peter J. Bickel
Publikováno v: Selected Works of Willem van Zwet ISBN: 9781461413134
We discuss a number of resampling schemes in which m = o(n) observations are resampled. We review nonparametric bootstrap failure and give results old and new on how the m out of n with replacement and without replacement bootstraps work. We extend w
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c305a8a83683f20067c8843d12e8a30e
https://doi.org/10.1007/978-1-4614-1314-1_17
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