Statistical Data Fusion
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€93.99
A01=Benjamin Kedem
A01=Michael Sverchkov
A01=Victor De Oliveira
Author_Benjamin Kedem
Author_Michael Sverchkov
Author_Victor De Oliveira
Bayesian
Category=PBT
Density Ratio
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Out of Sample Fusion
Semiparametric
Small Area
Tail Probability
Product details
- ISBN 9789813200180
- Publication Date: 20 Mar 2017
- Publisher: World Scientific Publishing Co Pte Ltd
- Publication City/Country: SG
- Product Form: Hardback
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"The book provides a comprehensive review of the DRM approach to data fusion. It is well written and easy to follow, although the technical details are not trivial. The authors did an excellent job in making a concise introduction of the statistical techniques in data fusion. The book contains several real data … Overall, I found that the book covers an important topic and the DRM is a promising tool in this area. Researchers on data fusion will surely find this book very helpful and I will use this book in studying with my PhD students."Journal of the American Statistical AssociationThis book comes up with estimates or decisions based on multiple data sources as opposed to more narrowly defined estimates or decisions based on single data sources. And as the world is awash with data obtained from numerous and varied processes, there is a need for appropriate statistical methods which in general produce improved inference by multiple data sources.The book contains numerous examples useful to practitioners from genomics. Topics range from sensors (radars), to small area estimation of body mass, to the estimation of small tail probabilities, to predictive distributions in time series analysis.
