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Multivariate Kernel Smoothing and Its Applications (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) by José E. Chacón, Tarn Duong is a nonfiction available to read on EtoBox.

What is Multivariate Kernel Smoothing and Its Applications (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) about?

Kernel smoothing has greatly evolved since its inception to become an essential methodology in the Data Science tool kit for the 21st century. Its widespread adoption is due to its fundamental role for multivariate exploratory data analysis, as well as the crucial role it plays in composite solutions to complex data challenges.**Multivariate Kernel Smoothing and Its Applications** offers a comprehensive overview of both aspects. It begins with a thorough exposition of the approaches to achieve the two basic goals of estimating probability density functions and their derivatives. The focus then turns to the applications of these approaches to more complex data analysis goals, many with a geometric/topological flavour, such as level set estimation, clustering (unsupervised learning), principal curves, and feature significance. Other topics, while not direct applications of density (derivative) estimation but sharing many commonalities with the previous settings, include classification (supervised learning), nearest neighbour estimation, and deconvolution for data observed with error. For a Data Scientist, each chapter contains illustrative Open Data examples that are analysed by the

Who reads Multivariate Kernel Smoothing and Its Applications (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)?

Author

José E. Chacón, Tarn Duong

Publisher

Chapman and Hall/CRC

Published

2018

Language

EN

ISBN

9780429485572

Category

nonfiction

Subjects

Mathematics, Science, Stem