Results 1 to 10 of about 22,159 (266)

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
J Franke
exaly   +7 more sources

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 ...
Wenceslao González Manteiga, Miguel A. Delgado   +1 more
exaly   +5 more sources

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
doaj   +1 more source

A Comparison of Nonparametric Statistics and Bootstrap Methods for Testing Two Independent Populations with Unequal Variance

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, Kantima Sodrung, Ampai Thongteeraparp   +2 more
doaj   +1 more source

Multi-Step-Ahead Prediction Intervals for Nonparametric Autoregressions via Bootstrap: Consistency, Debiasing, and Pertinence

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
doaj   +1 more source

Autoregressive wild bootstrap inference for nonparametric trends [PDF]

Journal of Econometrics, 2020
In this paper we propose an autoregressive wild bootstrap method to construct confidence bands around a smooth deterministic trend. The bootstrap method is easy to implement and does not require any adjustments in the presence of missing data, which makes it particularly suitable for climatological applications.
Friedrich, M., Smeekes, S., Urbain, J.
openaire   +7 more sources

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, E.J., Farrell, S., Ratcliff, R.   +2 more
openaire   +2 more sources

Nonparametric detection using empirical distributions and bootstrapping [PDF]

2017 25th European Signal Processing Conference (EUSIPCO), 2017
Publication in the conference proceedings of EUSIPCO, Kos island, Greece ...
Koivunen, Visa, Zoubir, Abdelhak, Gölz, Martin   +3 more
openaire   +3 more sources

Percentile Bootstrap Interval on Univariate Local Polynomial Regression Prediction

JTAM (Jurnal Teori dan Aplikasi Matematika), 2023
This study offers a new technique for constructing percentile bootstrap intervals to predict the regression of univariate local polynomials. Bootstrap regression uses resampling derived from paired and residual bootstrap methods.
Abil Mansyur, Elmanani Simamora, Ahmad Ahmad   +2 more
doaj   +1 more source

Computationally Efficient Bootstrap Expressions for Bandwidth Selection in Nonparametric Curve Estimation

Proceedings, 2018
Bootstrap methods are used for bandwidth selection in: (1) nonparametric kernel density estimation with dependent data (smoothed stationary bootstrap and smoothed moving blocks bootstrap), and (2) nonparametric kernel hazard rate estimation (smoothed ...
Inés Barbeito, Ricardo Cao
doaj   +1 more source