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Central limit theorem for asymmetric kernel functionals
(Escola de Pós-Graduação em Economia da FGV, 2004-02-01)
Asymmetric kernels are quite useful for the estimation of density functions with bounded support. Gamma kernels are designed to handle density functions whose supports are bounded from one end only, whereas beta kernels ...
Generating Random Variates via Kernel Density Estimation and Radial Basis Function Based Neural Networks
(Lecture Notes in Computer Science, 2019)
Nonparametric econometricsNonparametric econometrics
(Sociedade Brasileira de Econometria, 2002)
Density estimation via hybrid splines
(Gordon Breach Sci Publ LtdReadingInglaterra, 1998)
Nonparametric estimation of a surrogate density function in infinite-dimensional spaces
(Taylor & Francis Ltd, 2012-06)
A density function is generally not well defined in functional data context, but we can define a surrogate of a probability density, also called pseudo-density, when the small ball probability can be approximated by the ...
Generalized birnbaum-saunders kernel density estimators and an analysis of financial data
(ELSEVIER SCIENCE BV, 2013)
Generalized birnbaum-saunders kernel density estimators and an analysis of financial data
(ELSEVIER SCIENCE BV, 2013)
Adaptive estimation of a density function using beta kernels
(EDP SCIENCES, 2014)
On the performance of Kernel Density Estimation using Density Matrices
(Universidad Nacional de ColombiaBogotá - Ciencias - Maestría en Ciencias - EstadísticaDepartamento de EstadísticaFacultad de CienciasBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá, 2021-07-30)
Density estimation methods can be used to solve a variety of statistical and machine learning challenges. They can be used to tackle a variety of problems, including anomaly detection, generative models, semi-supervised ...