Results 11 to 20 of about 20,763 (296)
A Nonparametric Bootstrap Method for Heteroscedastic Functional Data [PDF]
Journal of Agricultural, Biological and Environmental Statistics, 2023 AbstractThe objective is to provide a nonparametric bootstrap method for functional data that consists of independent realizations of a continuous one-dimensional process. The process is assumed to be nonstationary, with a functional mean and a functional variance, and dependent.
Rubén Fernández‐Casal +2 more
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International Journal of Distributed Sensor Networks, 2013 This paper presents a nonparametric bootstrap multihop localization algorithm for large-scale wireless sensor networks (WSNs) in complex environments. Unlike most of the existing schemes, this work is based on the consideration that it is not feasible to
Yongji Ren +4 more
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Energies, 2020 Uncertainty of greenhouse gas (GHG) emissions was analyzed using the parametric Monte Carlo simulation (MCS) method and the non-parametric bootstrap method.
Kun Mo Lee +3 more
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Parametric and nonparametric bootstrap: an analysis of indoor air data from Kuwait
Kuwait Journal of Science, 2018 This paper discusses the performance of parametric and nonparametric bootstrap for confidence interval (CI) estimation applied to fine particulate matter (PM2.5) data.
Sana BuHamra +2 more
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Nonparametric bootstrap test for autoregressive additive models
Statistics in Transition new series, 2009 Additive autoregressive models are commonly used to describe and simplify the behaviour of a nonlinear time series. When the additive structure is chosen, and the model estimated, it is important to evaluate if it is really suitable to describe the observed data since additivity represents a strong assumption.
Bagnato L, PUNZO, ANTONIO
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Nonparametric Bootstrap Likelihood Estimation to Investigate the Chance Set-Up on Clustering Results [PDF]
IEEE Open Journal of the Computer SocietyClustering algorithms are widely used in the knowledge discovery domain, but concerns and questions about the validity of the results must be considered.
Ammar Elnour, Wencheng Yang, Yan Li
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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.
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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 +3 more
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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 +2 more
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Robust multivariate nonparametric tests for detection of two-sample location shift in clinical trials. [PDF]
PLoS ONE, 2018 This article presents and investigates performance of a series of robust multivariate nonparametric tests for detection of location shift between two multivariate samples in randomized controlled trials.
Xuejun Jiang +4 more
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