Items related to Sufficient Dimension Reduction (Chapman & Hall/CRC...
Sufficient Dimension Reduction (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) - Softcover
- PublisherRoutledge
- Publication date2020
- ISBN 10 0367734729
- ISBN 13 9780367734725
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages284
Buy New
View this item
US$ 74.84
Shipping:
US$ 8.38
From United Kingdom to U.S.A.
Search results for Sufficient Dimension Reduction (Chapman & Hall/CRC...
Stock Image
Sufficient Dimension Reduction (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
Seller: Majestic Books, Hounslow, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # 391756544
Quantity: 3 available
Stock Image
Sufficient Dimension Reduction: Methods and Applications with R
Published by
Taylor & Francis Ltd, 2020
ISBN 10: 0367734729
ISBN 13: 9780367734725
New
Paperback / softback
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days. 185. Seller Inventory # B9780367734725
Quantity: 1 available
Stock Image
Sufficient Dimension Reduction: Methods and Applications With R
Seller: Revaluation Books, Exeter, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: Brand New. 304 pages. 9.21x6.14x0.67 inches. In Stock. Seller Inventory # __0367734729
Quantity: 1 available
Seller Image
Sufficient Dimension Reduction
Published by
Taylor & Francis, Chapman And Hall/CRC, 2020
ISBN 10: 0367734729
ISBN 13: 9780367734725
New
Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that produce large datasets with a large number of variables. Sufficient Dimension Reduction: Methods and Applications with R introduces the basic theories and the main methodologies, provides practical and easy-to-use algorithms and computer codes to implement these methodologies, and surveys the recent advances at the frontiers of this field.FeaturesProvides comprehensive coverage of this emerging research field.Synthesizes a wide variety of dimension reduction methods under a few unifying principles such as projection in Hilbert spaces, kernel mapping, and von Mises expansion.Reflects most recent advances such as nonlinear sufficient dimension reduction, dimension folding for tensorial data, as well as sufficient dimension reduction for functional data.Includes a set of computer codes written in R that are easily implemented by the readers.Uses real data sets available online to illustrate the usage and power of the described methods.Sufficient dimension reduction has undergone momentous development in recent years, partly due to the increased demands for techniques to process high-dimensional data, a hallmark of our age of Big Data. This book will serve as the perfect entry into the field for the beginning researchers or a handy reference for the advanced ones. The authorBing Li obtained his Ph.D. from the University of Chicago. He is currently a Professor of Statistics at the Pennsylvania State University. His research interests cover sufficient dimension reduction, statistical graphical models, functional data analysis, machine learning, estimating equations and quasilikelihood, and robust statistics. He is a fellow of the Institute of Mathematical Statistics and the American Statistical Association. He is an Associate Editor for The Annals of Statistics and the Journal of the American Statistical Association. 304 pp. Englisch. Seller Inventory # 9780367734725
Quantity: 2 available
Stock Image
Sufficient Dimension Reduction (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
Seller: Books Puddle, New York, NY, U.S.A.
Seller rating 4 out of 5 stars
Condition: New. 1st edition NO-PA16APR2015-KAP. Seller Inventory # 26388891871
Quantity: 3 available
Stock Image
Sufficient Dimension Reduction (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
Seller: Biblios, Frankfurt am main, HESSE, Germany
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # 18388891861
Quantity: 3 available
Seller Image
Sufficient Dimension Reduction : Methods and Applications with R
Published by
Taylor & Francis, Chapman And Hall/CRC, 2020
ISBN 10: 0367734729
ISBN 13: 9780367734725
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that produce large datasets with a large number of variables. Sufficient Dimension Reduction: Methods and Applications with R introduces the basic theories and the main methodologies, provides practical and easy-to-use algorithms and computer codes to implement these methodologies, and surveys the recent advances at the frontiers of this field.FeaturesProvides comprehensive coverage of this emerging research field.Synthesizes a wide variety of dimension reduction methods under a few unifying principles such as projection in Hilbert spaces, kernel mapping, and von Mises expansion.Reflects most recent advances such as nonlinear sufficient dimension reduction, dimension folding for tensorial data, as well as sufficient dimension reduction for functional data.Includes a set of computer codes written in R that are easily implemented by the readers.Uses real data sets available online to illustrate the usage and power of the described methods.Sufficient dimension reduction has undergone momentous development in recent years, partly due to the increased demands for techniques to process high-dimensional data, a hallmark of our age of Big Data. This book will serve as the perfect entry into the field for the beginning researchers or a handy reference for the advanced ones. The authorBing Li obtained his Ph.D. from the University of Chicago. He is currently a Professor of Statistics at the Pennsylvania State University. His research interests cover sufficient dimension reduction, statistical graphical models, functional data analysis, machine learning, estimating equations and quasilikelihood, and robust statistics. He is a fellow of the Institute of Mathematical Statistics and the American Statistical Association. He is an Associate Editor for The Annals of Statistics and the Journal of the American Statistical Association. Seller Inventory # 9780367734725
Quantity: 2 available
Seller Image
Sufficient Dimension Reduction
Print on DemandSeller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that . Seller Inventory # 594600248
Quantity: Over 20 available