Results 281 to 290 of about 24,206 (303)

Smoothed Bootstrap for Survival Function Inference

2019 International Conference on Information and Digital Technologies (IDT), 2019
A 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, Tahani Coolen-Maturi, Frank P.A. Coolen   +2 more
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A smoothed bootstrap estimator for a studentized sample quantile

Annals of the Institute of Statistical Mathematics, 1993
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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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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A Smooth Block Bootstrap for Statistical Functionals and Time Series

Journal of Time Series Analysis, 2015
Unlike with independent data, smoothed bootstraps have received little consideration for time series, although data smoothing within resampling can improve bootstrap approximations, especially when target distributions depend on smooth population quantities (e.g., marginal densities).
Gregory, Karl B., Lahiri, Soumendra N., Nordman, Daniel J.   +2 more
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Applications of Smoothed Monotone Regression Splines and Smoothed Bootstrapping in Survival Analysis

1998
An estimate of a survival curve S(x) for censored data is given by the non-parametric Kaplan-Meier method, which provides an estimate of the empirical survival curve and estimators of the standard errors. We use the software package Confit, developed by WTI, which is designed to produce a smoothed approximating spline, subject to imposed constraints on
Donald E. Ramirez, Philip W. Smith
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The choice of smoothing parameter in nonparametric regression through Wild Bootstrap

Computational Statistics & Data Analysis, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wenceslao González-Manteiga, María Dolores Martínez Miranda, Ana Pérez González   +2 more
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Bootstrap methods in regression smoothing^∗

Journal of Nonparametric Statistics, 1993
A new smoothed bootstrap resampling plan is introduced in this paper in the context of nonparametric regression smoothing. A study of the rates of convergence for this method is carried out in a similar way to that made in Cao-Abad (1991) for the normal approximation, its plug-in approach and the wild bootstrap.
R. Cao-abad, W. González-Manteiga
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Bandwidth selection for the smoothed bootstrap percentile method

Computational Statistics & Data Analysis, 2001
Some 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.
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Bootstrapped and smoothed classification error rate estimators

Communications in Statistics - Simulation and Computation, 1988
The resubstitution estimator of classification error rates is known to have both an optimistic bias and a large variance. Modifications to this method have addressed these problems. the bootstrap estimator, for example, uses a resampling scheme to reduce bias, and the NS method uses a smoothing algorithm to reduce variance.
Steven M. Snapinn, James D. Knoke
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ASYMPTOTICS OF BOOTSTRAPPING MEAN ON SOME SMOOTHED EMPIRICAL DISTRIBUTION

Statistics & Risk Modeling, 1997
Summary: We considered bootstrapping the mean in the case where the unknown underlying distribution \(F\) is known to be continuous. Instead of resampling from the empirical distribution \(F_n\) formed from the given random sample \(\{X_1,\dots,X_n\}\), where \(X_i{\overset\text{i.i.d.}\sim}F\), we draw bootstrap samples from a smoothed empirical ...
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