Results 231 to 240 of about 9,169 (255)

The bootstrap: To smooth or not to smooth?

Biometrika, 1987
In the statistical bootstrap the sample is resampled with replacement. However, these samples with replacement are not drawn from the unknown distribution F itself but from the empirical distribution function \(F_ n\) of the observed data. Because \(F_ n\) is a discrete distribution, samples constructed from \(F_ n\) in the bootstrap simulations will ...
Silverman, B. W., Young, G. A.
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On the smoothed bootstrap

Journal of Statistical Planning and Inference, 2000
Let \(X_1,X_2,\dots, X_n\) be a sample of independent and identically distributed random variables. Denote by \(F\) the distribution function of \(X\). The authors consider the problem of estimating the parameter \(T(F)\) by a statistic \(T(\widehat F_n)\), where \(\widehat F_n(x)= \int^x_{-\infty} f_n(u) du\) and \(f_n(u)\) is the well-known kernel ...
El-Nouty, Charles, Guillou, Armelle
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Smoothed bootstrap Malmquist index based on DEA model to compute productivity of tax offices

Expert Systems With Applications, 2015
This paper analyses the productivity growth of the SUMA tax offices located in Spain evolved between 2004 and 2006 by using Malmquist Index based on Data Envelopment Analysis (DEA) models.
Ramon Fuentes, Adelaida Lillo-Bañuls
exaly   +2 more sources

Local Smoothing Using the Bootstrap

Communications in Statistics - Simulation and Computation, 2013
We 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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Smooth bootstrap methods for analysis of longitudinal data

Statistics in Medicine, 2007
AbstractIn analysis of longitudinal data, the variance matrix of the parameter estimates is usually estimated by the ‘sandwich’ method, in which the variance for each subject is estimated by its residual products. We propose smooth bootstrap methods by perturbing the estimating functions to obtain ‘bootstrapped’ realizations of the parameter estimates ...
Li, Yue, Wang, You-Gan
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Bootstrapping the distance between smooth bootstrap and sample quantile distribution

Probability Theory and Related Fields, 1989
The 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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Inference via kernel smoothing of bootstrap values

Computational Statistics & Data Analysis, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jeffrey S. Racine, James G. MacKinnon
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Smoothed Empirical Processes and the Bootstrap

2003
Based on a uniform functional central limit theorem (FCLT) for unbiased smoothed empirical processes indexed by a class.F of measurable functions defined on a linear metric space we present a consistency theorem for smoothed bootstrapped empirical processes.
Peter Gaenssler, Daniel Rost
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Histospline smoothing the Bayesian bootstrap

Biometrika, 1988
Summary: 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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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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