Results 151 to 160 of about 257,461 (188)
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Variable kernel density estimation
Australian & New Zealand Journal of Statistics, 2003SummaryThis paper considers the problem of selecting optimal bandwidths for variable (sample‐point adaptive) kernel density estimation. A data‐driven variable bandwidth selector is proposed, based on the idea of approximating the log‐bandwidth function by a cubic spline. This cubic spline is optimized with respect to a cross‐validation criterion.
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Kernel Density Estimation with Generalized Binning
Scandinavian Journal of Statistics, 1999We propose kernel density estimators based on prebinned data. We use generalized binning schemes based on the quantiles points of a certain auxiliary distribution function. Therein the uniform distribution corresponds to usual binning. The statistical accuracy of the resulting kernel estimators is studied, i.e.
Pawlak, M., Stadtmüller, U.
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Kernel Density Gradient Estimate
2011The aim of this contribution is to develop a method for a bandwidthmatrix choice for kernel estimate of the first partial derivatives of the unknown density.
Ivana Horová, Kamila Vopatová
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Kernel conditional density estimation
2021This thesis was scanned from the print manuscript for digital preservation and is copyright the author. Researchers can access this thesis by asking their local university, institution or public library to make a request on their behalf. Monash staff and postgraduate students can use the link in the References field.
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2001
In this chapter, we get our first taste of real analysis, starting with some results on the approximations of functions in L 1. The literature on this is vast, and a lot of it is ancient. The problem is that f cannot be approximated in L 1 by μ n , the empirical measure, as the total variation distance between any density f and any atomic measure (like
Luc Devroye, Gábor Lugosi
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In this chapter, we get our first taste of real analysis, starting with some results on the approximations of functions in L 1. The literature on this is vast, and a lot of it is ancient. The problem is that f cannot be approximated in L 1 by μ n , the empirical measure, as the total variation distance between any density f and any atomic measure (like
Luc Devroye, Gábor Lugosi
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Isolation Kernel Density Estimation
2021 IEEE International Conference on Data Mining (ICDM), 2021Kai Ming Ting +3 more
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Electroceramics for High-Energy Density Capacitors: Current Status and Future Perspectives
Chemical Reviews, 2021, Zhilun Lu, Linhao Li
exaly
Formulating energy density for designing practical lithium–sulfur batteries
Nature Energy, 2022Guangmin Zhou, Hao Chen
exaly