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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.
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Inference via kernel smoothing of bootstrap values
Computational Statistics & Data Analysis, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Racine, Jeffrey S., MacKinnon, James G.
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Histospline smoothing the Bayesian bootstrap
Biometrika, 1988Summary: This paper describes a version of the Bayesian bootstrap that assigns random Dirichlet mass uniformly across statistically equivalent blocks. The method requires prior knowledge that the underlying distribution is continuous with known compact support.
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Bootstrapping the distance between smooth bootstrap and sample quantile distribution
Probability Theory and Related Fields, 1989The normalized Kolmogorov-Smirnov and variational distance between the distribution of the sample q-quantile and the pertaining smooth bootstrap distribution are asymptotically distributed like the absolute value of a normal random variable. The distribution functions of these random distances may serve as measures of the accuracy of the bootstrap ...
Falk, M., Reiss, R.-D.
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Optimizing the smoothed bootstrap
Annals of the Institute of Statistical Mathematics, 1995zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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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.
Andrés M. Alonso, Antonio Cuevas
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Smoothed Bootstrap for Survival Function Inference
2019 International Conference on Information and Digital Technologies (IDT), 2019A new generalized smoothed bootstrap technique is presented for data including right-censored observations. The method is based on Banks’ bootstrap [2] and the right-censoring A (n) assumption introduced by [7], which is a generalization of Hill’s A (n) assumption [12].
Asamh S.M. Al Luhayb +2 more
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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, Kim-Anh Do
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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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Local Smoothing Using the Bootstrap
Communications in Statistics - Simulation and Computation, 2013We consider the problem of data-based choice of the bandwidth of a kernel density estimator, with an aim to estimate the density optimally at a given design point. The existing local bandwidth selectors seem to be quite sensitive to the underlying density and location of the design point.
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