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Optimal choice between parametric and non-parametric bootstrap estimates
Mathematical Proceedings of the Cambridge Philosophical Society, 1994AbstractA parametric bootstrap estimate (PB) may be more accurate than its non-parametric version (NB) if the parametric model upon which it is based is, at least approximately, correct. Construction of an optimal estimator based on both PB and NB is pursued with the aim of minimizing the mean squared error.
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Parametric bootstrap for reliability assessment
2010The article concerns the evaluation of reliability for stress-strength models. A parametric bootstrap approach is suggested for the interval estimation of reliability, and its performance is checked and compared to other procedures available from literature through a simulation study performed on artificial data.
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An application of weighted bootstrap method in semi-parametric model
Information Sciences, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Non-parametric and unsupervised Bayesian classification with Bootstrap sampling
Image and Vision Computing, 2004Abstract In this paper, we propose a non-parametric and unsupervised Bayesian classification based on the principle of Bootstrap sampling (BS) which reduces the dependence effect of pixels in real images, and reduces the classification time. Given an original image, we randomly select a small representative set of pixels.
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A parametric version of jackknife-after-bootstrap
1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274), 2002openaire +1 more source
Validity of the parametric bootstrap for goodness-of-fit testing in semiparametric models
Annales De L'institut Henri Poincare (B) Probability and Statistics, 2008Christian Genest, Bruno Remillard
exaly