Results 11 to 20 of about 46,105 (114)
Kernel Density Derivative Estimation of Euler Solutions
Applied Sciences, 2023 Conventional Euler deconvolution is widely used for interpreting profile, grid, and ungridded potential field data. The Tensor Euler deconvolution applies additional constraints to the Euler solution using all gravity vectors and the full gravity ...
Shujin Cao +7 more
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Entropy, 2008 At the heart of many ICA techniques is a nonparametric estimate of an information measure, usually via nonparametric density estimation, for example, kernel density estimation.
Julian Sorensen
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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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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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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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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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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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Proceedings, 2018 Bootstrap methods are used for bandwidth selection in: (1) nonparametric kernel density estimation with dependent data (smoothed stationary bootstrap and smoothed moving blocks bootstrap), and (2) nonparametric kernel hazard rate estimation (smoothed ...
Inés Barbeito, Ricardo Cao
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Improved parameter estimation of Time Dependent Kernel Density by using Artificial Neural Networks
Journal of Finance and Data Science, 2018 Time Dependent Kernel Density Estimation (TDKDE) used in modelling time-varying phenomenon requires two input parameters known as bandwidth and discount to perform.
Xing Wang +2 more
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Exploring Violent and Property Crime Geographically
Nordic Journal of Studies in Policing, 2021 There are multiple geographical crime prediction techniques to use and comparing different prediction techniques therefore becomes important. In the current study we compared the accuracy (Predictive Accuracy Index) and precision (Recapture Rate Index ...
Maria Camacho Doyle +2 more
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