Journal Article10.1080/01621459.1996.10476701
A Brief Survey of Bandwidth Selection for Density Estimation
TL;DR: In this article, the authors recommend a "solve-the-equation" plug-in bandwidth selector as being most reliable in terms of overall performance for kernel density estimation.
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Abstract: There has been major progress in recent years in data-based bandwidth selection for kernel density estimation. Some “second generation” methods, including plug-in and smoothed bootstrap techniques, have been developed that are far superior to well-known “first generation” methods, such as rules of thumb, least squares cross-validation, and biased cross-validation. We recommend a “solve-the-equation” plug-in bandwidth selector as being most reliable in terms of overall performance. This article is intended to provide easy accessibility to the main ideas for nonexperts.
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Citations
New approach for bandwidth selection in the kernel density estimation based on
Hamza Dhaker,Universit Cheikh Anta Diop de Dakar,Papa Ngom,El Hadji Deme,Malick Mbodj +4 more
- 10 Jun 2018
TL;DR: The idea behind this method is to generalize the LSCV method, using the measure of ; divergence β HAMZA DHAKER et al. 58 and to see the improvement in the method, to select the optimal bandwidth for the KDE.
Conditional density estimation with covariate measurement error
Xianzheng Huang,Haiming Zhou +1 more
TL;DR: An R package, lpme, is developed for implementing all considered methods and extensive simulation studies are carried out to compare the proposed estimators with naive estimators that ignore measurement error, which provide empirical evidence for the effectiveness of the proposed bandwidth selection methods.
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Ranking of power system loads based on their influence on power system stability
Yue Zhu
- 01 Jan 2019
6
From finite sample to asymptotics: A geometric bridge for selection criteria in spline regression
TL;DR: In this paper, the connection between finite-sample properties of selection criteria and their asymptotic counterparts was studied under the setting of spline regression, focusing on bridging the gap between the two.
Desigualdad, diversidad y convergencia: (más) instrumentos de medida -estadística descriptiva-. *
Francisco J. Goerlich,Francisco J. Goerlich Gisbert +1 more
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TL;DR: Goerlich as mentioned in this paper described a simple reference model that acomodates such a variable, the analysis of variance, and continues by considering the concept of β-convergence and its implementation in the context of regresion models.
6
References
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Grace Wahba
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TL;DR: In this paper, a theory and practice for the estimation of functions from noisy data on functionals is developed, where convergence properties, data based smoothing parameter selection, confidence intervals, and numerical methods are established which are appropriate to a number of problems within this framework.
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Multivariate Density Estimation, Theory, Practice and Visualization
TL;DR: Representation and Geometry of Multivariate Data.
4.5K