Results 221 to 230 of about 9,169 (255)
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On the bootstrap and smoothed bootstrap
Communications in Statistics - Theory and Methods, 1989The standard bootstrap and two commonly used types of smoothed bootstrap are investigated. The saddlepoint approximations are used to evaluate the accuracy of the three bootstrap estimates of the density of a sample mean. The optimal choice for the smoothing parameter is obtained when smoothing is useful in reducing the mean squared error.
Suojin Wang
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On smoothed bootstrap for density functionals
Journal of Nonparametric Statistics, 2003We analyze, from both theoretical and practical point of view, the use of the smoothed bootstrap in the estimation of a functional T(f) of the underlying density. We consider a plug-in approach based on the use of an estimator of type T(fˆ n ) where fˆ n is a nonparametric (kernel) estimator of f.
Andres M Alonso, Antonio Cuevas
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Importance resampling for the smoothed bootstrap
Journal of Statistical Computation and Simulation, 1992Alternative methods of estimating properties of unknown distributions include the bootstrap and the smoothed bootstrap. In the standard bootstrap setting, Johns (1988) introduced an importance resam¬pling procedure that results in more accurate approximation to the bootstrap estimate of a distribution function or a quantile.
Zehua Chen
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On Bootstrapping Using Smoothed Bootstrap
2019The standard bootstrap method was introduced as a resampling method for statistical inference; it is a computer based method for assigning measures of accuracy to statistical estimates. The bootstrap sample is obtained by randomly sampling n times, with replacement, from the original sample.
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A smoothed bootstrap test for independence based on mutual information
Computational Statistics & Data Analysis, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wu, EHC, Yu, PLH, Li, WK
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Bandwidth selection for the smoothed bootstrap percentile method
Computational Statistics and Data Analysis, 2001Some applications of the bootstrap involve smoothing the estimated distribution that is resampled, a method known as the smoothed bootstrap. Recently, the effect of resampling a kernel smoothed distribution was evaluated through expansions for the coverage of bootstrap percentile confidence intervals.
Alan M Polansky
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Smoothed bootstrap for right-censored data
Communications in Statistics - Theory and Methods, 2023 A smoothed bootstrap method is introduced for right-censored data based on the right-censoring-A(n) assumption introduced by Coolen and Yan, which is a generalization of Hill’s A(n) assumption for right-censored data.
Asamh Saleh M. Al Luhayb +2 more
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Smoothed bootstrap consistency through the convergence in mallows metric of smooth estimates
Journal of Nonparametric Statistics, 2000This article examines smoothed bootstrap consistency of the sample mean, regular functions of the sample mean and multiple regression models. We use Mallows metric convergence of the empirical distribution, plugged-in by the bootstrap method, towards the theoretical distribution of the data.
Daniele De Martini
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Iterated smoothed bootstrap confidence intervals for population quantiles [PDF]
Annals of Statistics, 2005 This paper investigates the effects of smoothed bootstrap iterations on coverage probabilities of smoothed bootstrap and bootstrap-t confidence intervals for population quantiles, and establishes the optimal kernel band-widths at various stages of the ...
Lee, SMS, Ho, YHS
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International Statistical Review / Revue Internationale de Statistique, 1992
Summary: The question of smoothing when using the non-parametric version of the bootstrap for estimation of population functionals is reconsidered. In general, there is no global preference for procedures based on a smoothed version of the empirical distribution rather than the empirical distribution itself.
de Angelis, Daniela, Young, G. Alastair
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Summary: The question of smoothing when using the non-parametric version of the bootstrap for estimation of population functionals is reconsidered. In general, there is no global preference for procedures based on a smoothed version of the empirical distribution rather than the empirical distribution itself.
de Angelis, Daniela, Young, G. Alastair
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