Results 21 to 30 of about 257,461 (188)
Kernel adjusted density estimation [PDF]
Statistics & Probability Letters, 2011 We propose and study a kernel estimator of a density in which the kernel is adapted to the data but not fixed. The smoothing procedure is followed by a location-scale transformation to reduce bias and variance. The new method naturally leads to an adaptive choice of the smoothing parameters which avoids asymptotic expansions.
Srihera, Ramidha, Stute, Winfried
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Matematika, 2018 Abstrak. Pada penelitian yang dilakukan oleh Setiawan dkk, menyatakan bahwa metode loss distribution approach dengan pendekatan kernel density estimation mampu menghasilkan nilai economic capital yang lebih efisien sebesar 1,6% - 3,2% dibandingkan dengan
Erwan Setiawan, Ramdhan F Suwarman
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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 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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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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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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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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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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Sparse kernel density estimation technique based on zero-norm constraint [PDF]
, 2010 A sparse kernel density estimator is derived based on the zero-norm constraint, in which the zero-norm of the kernel weights is incorporated to enhance model sparsity.
Chen, S, Harris, C J, Hong, Xia
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Confidence Intervals for Kernel Density Estimation [PDF]
The Stata Journal: Promoting communications on statistics and Stata, 2004 This article describes asciker and bsciker, two programs that enrich the possibility for density analysis using Stata. asciker and bsciker compute asymptotic and bootstrap confidence intervals for kernel density estimation, respectively, based on the theory of kernel density confidence intervals estimation developed in Hall (1992b)and Horowitz (2001).
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