Statistical Data Fusion; a new book for graduate students, researchers, practitioners of statistics, engineers, scientists; has just been published by World Scientific. The book is co-written by ISR-affiliated Professor Benjamin Kedem (Math); his former student Victor De Oliveira (Math Ph.D. 1997), a professor at the University of Texas at San Antonio; and Michael Sverchkov of the U.S. Department of Labor Bureau of Labor Statistics’ Mathematical Statistics Research Center.
Because 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 taking as input the information from many sources. This new 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. It contains numerous examples useful to those working in genomics, sensors (radars), small area estimation of body mass, estimation of small tail probabilities, and predictive distributions in time series analysis.
A Reference Distribution and its Many Distortions
Inference for Weighted Systems of Distributions
Some Asymptotic Results
Out of Sample Fusion
Bayesian Inference for Weighted Systems of Distributions
Small Area Estimation
The ISBN number is 978-981-3200-18-0.
Kedem, De Oliveira win Canadian Journal of Statistics Award
Alumna Mingyan Liu named ECE chair at University of Michigan
Best paper award for Bergbreiter, St. Pierre, Gosrich at Hilton Head workshop
Alum Mingyan Liu is PI for Multiscale Network Games of Collusion and Competition MURI
Alumnus Philip Twu's exciting career in space robotics
ISR researchers win additional $948K NSF Neural and Cognitive Systems grant
Alum Leonard Petnga to join University of Alabama Huntsville faculty
Nima Ghalichechian begins Ohio State tenure-track position
Alum Domenic Forte receives NSF CAREER Award
Alumnus Fumin Zhang promoted to full professor at Georgia Tech
January 20, 2017