Nonparametric Kernel Density Estimation and Its Computational Aspects

Nonparametric Kernel Density Estimation and Its Computational Aspects
Author :
Publisher : Springer
Total Pages : 197
Release :
ISBN-10 : 9783319716886
ISBN-13 : 3319716883
Rating : 4/5 (883 Downloads)

Book Synopsis Nonparametric Kernel Density Estimation and Its Computational Aspects by : Artur Gramacki

Download or read book Nonparametric Kernel Density Estimation and Its Computational Aspects written by Artur Gramacki and published by Springer. This book was released on 2017-12-21 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Nonparametric Kernel Density Estimation and Its Computational Aspects Related Books

Nonparametric Kernel Density Estimation and Its Computational Aspects
Language: en
Pages: 197
Authors: Artur Gramacki
Categories: Technology & Engineering
Type: BOOK - Published: 2017-12-21 - Publisher: Springer

GET EBOOK

This book describes computational problems related to kernel density estimation (KDE) – one of the most important and widely used data smoothing techniques. A
Statistical Theory and Computational Aspects of Smoothing
Language: en
Pages: 273
Authors: Wolfgang Härdle
Categories: Business & Economics
Type: BOOK - Published: 2013-03-08 - Publisher: Springer Science & Business Media

GET EBOOK

One of the main applications of statistical smoothing techniques is nonparametric regression. For the last 15 years there has been a strong theoretical interest
Smoothing Methods in Statistics
Language: en
Pages: 349
Authors: Jeffrey S. Simonoff
Categories: Mathematics
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

GET EBOOK

The existence of high speed, inexpensive computing has made it easy to look at data in ways that were once impossible. Where once a data analyst was forced to m
Nonparametric Functional Estimation and Related Topics
Language: en
Pages: 691
Authors: G.G Roussas
Categories: Mathematics
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

GET EBOOK

About three years ago, an idea was discussed among some colleagues in the Division of Statistics at the University of California, Davis, as to the possibility o
Kernel Smoothing in MATLAB
Language: en
Pages: 242
Authors: Ivanka Horova
Categories: Mathematics
Type: BOOK - Published: 2012 - Publisher: World Scientific

GET EBOOK

Methods of kernel estimates represent one of the most effective nonparametric smoothing techniques. These methods are simple to understand and they possess very