Results 11 to 20 of about 49,315 (263)
Robust kernel density estimation [PDF]
2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008 We propose a method for nonparametric density estimation that exhibits robustness to contamination of the training sample. This method achieves robustness by combining a traditional kernel density estimator (KDE) with ideas from classical $M$-estimation.
JooSeuk Kim, Clayton D. Scott
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Graph Bundling by Kernel Density Estimation [PDF]
Computer Graphics Forum, 2012 AbstractWe present a fast and simple method to compute bundled layouts of general graphs. For this, we first transform a given graph drawing into a density map using kernel density estimation. Next, we apply an image sharpening technique which progressively merges local height maxima by moving the convolved graph edges into the height gradient flow ...
Christophe Hurter +2 more
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Research of comparative analysis of nonparametric density estimation by applying Monte Carlo method
Lietuvos Matematikos Rinkinys, 2013 This paper presents nonparametric statistical estimation of distribution density. The Monte Carlo method is used to show the effects of kernel function for multimodal kernel density estimation.
Indrė Drulytė, Tomas Ruzgas
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Estimation of Environmental Exposure: Interpolation, Kernel Density Estimation, or Snapshotting. [PDF]
Ann GIS, 2019 Shi X +7 more
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Varying kernel density estimation on [PDF]
Statistics & Probability Letters, 2012 In this article a new nonparametric density estimator based on the sequence of asymmetric kernels is proposed. This method is natural when estimating an unknown density function of a positive random variable. The rates of Mean Squared Error, Mean Integrated Squared Error, and the L1-consistency are investigated.
Robert, Mnatsakanov +1 more
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Journal of Statistical Software, 2018 evmix is an R package (R Core Team 2017) with two interlinked toolsets: i) for extreme value modeling and ii) kernel density estimation. A key issue in univariate extreme value modeling is the choice of threshold beyond which the asymptotically motivated
Yang Hu, Carl Scarrott
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Kernel distribution density estimation based on cross-validation
Lietuvos Matematikos Rinkinys, 2000 The kernel density estimation procedure is proposed. Parameter selection method based on cross-validation technique is analyzed. The results of investigation by simulation means are discussed.
Mindaugas Kavaliauskas
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Adaptive Kernel Density Estimation [PDF]
The Stata Journal: Promoting communications on statistics and Stata, 2003 This insert describes the module akdensity. akdensity extends the official kdensity that estimates density functions by the kernel method. The extensions are of two types: akdensity allows the use of an “adaptive kernel” approach with varying, rather than fixed, bandwidths; and akdensity estimates pointwise variability bands around the estimated ...
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Kernel Density Estimation on the Siegel Space with an Application to Radar Processing
Entropy, 2016 This paper studies probability density estimation on the Siegel space. The Siegel space is a generalization of the hyperbolic space. Its Riemannian metric provides an interesting structure to the Toeplitz block Toeplitz matrices that appear in the ...
Emmanuel Chevallier +3 more
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EEG Signal Enhancement Using OWA Filter [PDF]
ITM Web of Conferences, 2021 Biomedical signal monitoring and recording are an integral part of medical diagnosis and treatment control mechanisms. For this, enhanced signals with appropriate peak preservation are required.
Yadav Soham +3 more
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