Principal Component Analysis

Descripción

Neuware - Principal component analysis is central to the study of multivariate data. Although one of the earliest multivariate techniques, it continues to be the subject of much research, ranging from new model-based approaches to algorithmic ideas from neural networks. It is extremely versatile, with applications in many disciplines. The first edition of this book was the first comprehensive text written solely on principal component analysis. The second edition updates and substantially expands the original version, and is once again the definitive text on the subject. It includes core material, current research and a wide range of applications. Its length is nearly double that of the first edition. Researchers in statistics, or in other fields that use principal component analysis, will find that the book gives an authoritative yet accessible account of the subject. It is also a valuable resource for graduate courses in multivariate analysis. The book requires some knowledge of matrix algebra. Ian Jolliffe is Professor of Statistics at the University of Aberdeen. He is author or co-author of over 60 research papers and three other books. His research interests are broad, but aspects of principal component analysis have fascinated him and kept him busy for over 30 years.

N° de ref. del artículo 9780387954424

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Detalles bibliográficos

Título

Principal Component Analysis

Editor

Springer New York Okt 2002

Fecha de publicación

2002

Idioma

Inglés

ISBN 10

0387954422

ISBN 13

9780387954424

Encuadernación

Buch

Edición

2ª Edición

Estado

Neu

Dimensiones

241 mm an. × 159 al. × 38 l. 241 milímetros de ancho por 159 de alto por 38 de largo

Peso

936 gramos

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