Kernel estimation of density level sets
Journal of Multivariate Analysis, 2006 Let $f$ be a multivariate density and $f\_n$ be a kernel estimate of $f$ drawn from the $n$-sample $X\_1,...,X\_n$ of i.i.d. random variables with density $f$. We compute the asymptotic rate of convergence towards 0 of the volume of the symmetric difference between the $t$-level set $\{f\geq t\}$ and its plug-in estimator $\{f\_n\geq t\}$.
openaire +4 more sources
Forest Fire Risk Mapping by Kernel Density Estimation
Croatian Journal of Forest Engineering, 2011 When evaluating wildland fires, well prepared forest fire risk maps are regarded as one of the most valuable tools for forest managers, and during the production stage of these maps, association between historical fire data and other factors, such as ...
Semih Kuter +2 more
doaj
Weighted 2D-kernel density estimations provide a new probabilistic measure for epigenetic age
Genome BiologyEpigenetic aging signatures provide insights into human aging, but traditional clocks rely on linear regression of DNA methylation levels, assuming linear trajectories.
Juan-Felipe Perez-Correa +6 more
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AxiomsThe article investigates the accuracy of nonparametric univariate density estimation methods applied to various Gaussian mixture models. A comprehensive comparative analysis is performed for four popular estimation approaches: adaptive kernel density ...
Tomas Ruzgas +3 more
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Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC [PDF]
Kernel density estimation for multivariate data is an important technique that has a wide range of applications in econometrics and finance. However, it has received significantly less attention than its univariate counterpart.
Maxwell L. King, +2 more
core
Support vector data description with kernel density estimation (SVDD-KDE) control chart for network intrusion monitoring. [PDF]
Sci Rep, 2023 Ahsan M, Khusna H, Wibawati, Lee MH.
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Nonparametric Estimation of Risk-Neutral Densities [PDF]
This chapter deals with nonparametric estimation of the risk neutral density. We present three different approaches which do not require parametric functional assumptions on the underlying asset price dynamics nor on the distributional form of the risk ...
Maria Grith +2 more
core
Incipient Fault Detection in a Hydraulic System Using Canonical Variable Analysis Combined with Adaptive Kernel Density Estimation. [PDF]
Sensors (Basel), 2023 Wang J +5 more
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How the Distribution of After-Tax Income Changed over the 1990s Business Cycle: A Comparison of the United States, Great Britain, Germany and Japan [PDF]
Using kernel density estimation we find that over their 1990s business cycles the entire distribution of after-tax (disposable) income moved to the right in the United States and Great Britain while inequality declined.
Ludmila Rovba +2 more
core
A close contact identification algorithm using kernel density estimation for the ship passenger health. [PDF]
J King Saud Univ Comput Inf Sci, 2023 Lin Q, Son J.
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