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Multivariate Kernel Smoothing and Its Applications (Paperback)
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Multivariate Kernel Smoothing and Its Applications (Paperback)
Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Expected to ship within 12 - 17 working days
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Total price: R1,492
Discovery Miles: 14 920
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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 most appropriate kernel
smoothing method. The emphasis is always placed on an intuitive
understanding of the data provided by the accompanying statistical
visualisations. For a reader wishing to investigate further the
details of their underlying statistical reasoning, a graduated
exposition to a unified theoretical framework is provided. The
algorithms for efficient software implementation are also
discussed. Jose E. Chacon is an associate professor at the
Department of Mathematics of the Universidad de Extremadura in
Spain. Tarn Duong is a Senior Data Scientist for a start-up which
provides short distance carpooling services in France. Both authors
have made important contributions to kernel smoothing research over
the last couple of decades.
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