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
Applying particle swarm optimization to determine the bandwidth parameter in probability density estimation
Hai-Li Liang,Xian-Min Shen +1 more
- 10 Jul 2011
TL;DR: Five particle swarm optimization (PSO) algorithms are applied and Gaussian PSO with jump methods can obtain the better estimations than other PSO algorithms, and comparative results show that their strategies are well-performed.
4
A new bandwidth selector in hazard estimation
TL;DR: In this article, a new bandwidth selector was proposed for density estimation in the context of multivariate hazard rate estimation with right-censored data, and the relative rate of convergence of this new selector to the theoretical bandwidth that minimizes the MISE in square root n was proved.
4
Statistical Inference for Nonstationary Processes
Jan Beran,Yuanhua Feng,Sucharita Ghosh,Rafał Kulik +3 more
- 01 Jan 2013
TL;DR: This chapter discusses statistical inference for nonstationary processes, which is of particular interest for long-memory processes because long-range dependence often generates sample paths that mimic certain features of nonstationarity.
4
Three-dimensional simulation of nonwoven fabrics using a greedy approximation of the distribution of fiber directions
TL;DR: A novel greedy algorithm for estimating a sparse representation of the PDF is introduced and it is shown that the introduced sparsity ansatz leads to a reduction of the computation time for 100 fibers from around 80 days to 2.5 hours.
4
Convergence rates for average square errors for kernel smoothing estimators
Tae Yoon Kim,Dennis D. Cox +1 more
TL;DR: Convergence rate of ASE and difference between ISE and ASE are studied, which reveals that curse of dimension affects square errors in regression setting and there exists a cutoff point in dimension where A SE and ISE are no longer asymptotically equivalent.
4
References
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Bernard W. Silverman
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Grace Wahba
- 01 Mar 1990
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.
6.9K
Multivariate Density Estimation, Theory, Practice and Visualization
TL;DR: Representation and Geometry of Multivariate Data.
4.5K