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Nonparametric Kernel Density Estimation and Its Computational Aspects

Language EnglishEnglish
Book Paperback
Book Nonparametric Kernel Density Estimation and Its Computational Aspects Artur Gramacki
Libristo code: 21136319
Publishers Springer International Publishing AG, June 2019
This book describes computational problems related to kernel density estimation (KDE) - one of the m... Full description
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This book describes computational problems related to kernel density estimation (KDE) - one of the most important and widely used data smoothing techniques. A very detailed description of novel FFT-based algorithms for both KDE computations and bandwidth selection are presented. The theory of KDE appears to have matured and is now well developed and understood. However, there is not much progress observed in terms of performance improvements. This book is an attempt to remedy this. The book primarily addresses researchers and advanced graduate or postgraduate students who are interested in KDE and its computational aspects. The book contains both some background and much more sophisticated material, hence also more experienced researchers in the KDE area may find it interesting. The presented material is richly illustrated with many numerical examples using both artificial and real datasets. Also, a number of practical applications related to KDE are presented.

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About the book

Full name Nonparametric Kernel Density Estimation and Its Computational Aspects
Author Artur Gramacki
Language English
Binding Book - Paperback
Date of issue 2019
Number of pages 176
EAN 9783319890944
Libristo code 21136319
Publishers Springer International Publishing AG
Weight 326
Dimensions 155 x 235 x 12

Categories

Computing & Information Technology > Computer science > Artificial intelligence
Computing & Information Technology > Databases
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