Roger Lee Berger is an American statistician and professor, co-author of Statistical Inference, first published in 1990 with collaborator George Casella.
[2] Building on the work of his advisor Shanti Swarup Gupta in subset selection,[3] Berger wrote Minimax, Admissible, and Gamma-Minimax Multiple Decision Rules to complete his doctoral studies.
[6] Berger and George Casella met at Purdue and became fast friends, studying statistics together.
In 1983 at the Eastern North American Region (ENAR) conference of the International Biometric Society, Casella asked Berger to co-author a new master's level introductory text to statistical inference, hoping to revise and improve Hogg and Craig's Introduction to Mathematical Statistics.
[3] They continued to publish papers together, touching on topics such as generalized means and the reconciliation of Bayesian and frequentist testing, until Casella's death in 2012.