|
Robert Tibshirani is a Professor in the Departments of Statistics and Health Research and Policy at Stanford University. He was a Professor at the University of Toronto from 1985 to 1998. In his work, he develops statistical tools for the analysis of complex datasets, most recently in genomics and proteomics.
His most well-known contributions are the LASSO method, which proposed the use of L¹ penalization in regression and related problems, and Significance Analysis of Microarrays. He has also co-authored three well-known books: "Generalized Additive Models", "An Introduction to the Bootstrap", and "The Elements of Statistical Learning", the last of which is available for free from the author's website.
His son, Ryan Tibshirani, is currently an Assistant Professor at Carnegie Mellon University in the department of Statistics, jointly in the department of the Machine Learning.
|
