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Properties of the nonparametric autoregressive bootstrap [PDF]
Journal of Time Series Analysis, 2002 For nonparametric autoregression, we investigate a model based bootstrap procedure (`autoregressive bootstrap') that mimics the complete dependence structure of the original time series. We give consistency results for uniform bootstrap confidence bands of the autoregression function based on kernel estimates of the autoregression function. This result
Jens-Peter Kreis
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A fuzzy nonparametric Shewhart chart based on the bootstrap approach [PDF]
International Journal of Applied Mathematics and Computer Science, 2015 In this paper, we consider a nonparametric Shewhart chart for fuzzy data. We utilize the fuzzy data without transforming them into a real-valued scalar (a representative value).
Wang Dabuxilatu, Hryniewicz Olgierd
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Significance testing in nonparametric regression based on the bootstrap
Annals of Statistics, 2001 We propose a test for selecting explanatory variables in nonparametric regression. The test does not need to estimate the conditional expectation function given all the variables but only those which are significant under the null hypothesis. This feature is compntationally convenient and solves, in part, the problem of the "curse of dimensionality ...
MIGUEL A Delgado
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Naïve nonparametric bootstrap model weights are biased. [PDF]
Biometrics, 2004 (AIC) and R is the total number of candidate models (e.g., Burnham and Anderson, 2001). Recent work in statistical biology has suggested that model weights can also be obtained from the nonparametric bootstrap (e.g., Buckland, Burnham, and Augustin, 1997). The nonparametric bootstrap method samples, with replacement, n values from the observed data x =
Wagenmakers EJ, Farrell S, Ratcliff R.
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On Bootstrap Confidence Intervals in Nonparametric Regression
Annals of Statistics, 1992 A pivotal approach to nonparametric regression is considered. Some of the theoretical advantages of this approach are pointed out, among them a reduction in the error of the bootstrap distribution function estimate and a reduction in coverage error of confidence interval.
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Nonparametric quantile regression captures regional variability and scaling deviations in Atlantic surfclam length–weight relationships [PDF]
Scientific ReportsThe universality of the allometric model for describing the length–weight relationship in marine species has been questioned, particularly for some invertebrates such as sea urchins, clams, and barnacles.
Gorka Bidegain +6 more
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Rate of Convergence for the Wild Bootstrap in Nonparametric Regression
Annals of Statistics, 1991 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Nonparametric bootstrap confidence bands for unfolding sphere size distributions [PDF]
Opuscula Mathematica, 2021 The stereological inverse problem of unfolding the distribution of spheres radii from measured planar sections radii, known as the Wicksell's corpuscle problem, is considered.
Jakub Wojdyła
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International Journal of Analysis and Applications, 2023 The common parametric statistics used for testing two independent populations have often required the assumptions of normality and equal variances. Nonparametric tests have been used when assumptions of parametric tests cannot be achieved.
Wandee Wanishsakpong +2 more
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Stats, 2023 To address the difficult problem of the multi-step-ahead prediction of nonparametric autoregressions, we consider a forward bootstrap approach. Employing a local constant estimator, we can analyze a general type of nonparametric time-series model and ...
Dimitris N. Politis, Kejin Wu
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