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Smoothing of Multivariate Data
Jussi Sakari Klemelä
€ 216.12
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Description for Smoothing of Multivariate Data
Hardcover. This comprehensive resource provides the algorithmic methods and state-of-the-art tools to successfully visualize statistical data. The coverage offers insight into underlying processes of density estimation, emphasizing use of visualization tools rather than only the theoretical concepts of classification and regression. Series: Wiley Series in Probability and Statistics. Num Pages: 604 pages, Illustrations. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 242 x 159 x 23. Weight in Grams: 980.
An applied treatment of the key methods and state-of-the-art tools for visualizing and understanding statistical data
Read moreSmoothing of Multivariate Data provides an illustrative and hands-on approach to the multivariate aspects of density estimation, emphasizing the use of visualization tools. Rather than outlining the theoretical concepts of classification and regression, this book focuses on the procedures for estimating a multivariate...
Product Details
Format
Hardback
Publication date
2009
Publisher
John Wiley and Sons Ltd United Kingdom
Number of pages
604
Condition
New
Series
Wiley Series in Probability and Statistics
Number of Pages
640
Place of Publication
New York, United States
ISBN
9780470290880
SKU
V9780470290880
Shipping Time
Usually ships in 7 to 11 working days
Ref
99-50
About Jussi Sakari Klemelä
Jussi KlemelÄ, PhD, is Researcher in the Department of Mathematical Sciences at the University of Oulu, Finland. Dr. Klemelä has authored or coauthored numerous journal articles on his areas of research interest, which include density estimation and the implementation of cutting edge visualization tools.
Reviews for Smoothing of Multivariate Data
"Overall, the book complements existing books on nonparametric density estimation with its focus on multivariate data, visualization and sieve-type estimators." (Mathematical Reviews, 2011) "The book is suitable for courses in data analysis, multivariate analysis, and nonparametric statistics at the upper-undergraduate and graduate levels. Since it combines mathematical analysis with practical implementation it is also recommended to practitioners and researchers in...
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