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TREVOR HASTIE
The John A. Overdeck Professor
Professor of
Statistics
Professor of Biomedical Data Science
Stanford University
Welcome to my home page. I have a joint appointment in the Department
of Statistics at Stanford University, and the Department of Biomedical Data Science in the Stanford School of Medicine.
I have been on the faculty at Stanford since August, 1994. Before that
I was a member of the technical staff at AT&T Bell Laboratories,
Murray Hill, New Jersey, where I worked for 9 years.
In 2018 I was elected to the United States National Academy of
Sciences. I am a dual citizen of the United States and South
Africa. For more
details, click on the link to my biography.
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Interview with Sir David Cox (7/15/1924 - 1/18/2022) in Fall 2021. This 20 minute interview
with the 97 year old legend by Rob Tibshirani and me was recorded for the second edition of our
free online course on
Statistical
Learning, and appears in the chapter on Survival Analysis. David
Cox was at home in Oxford, and the recording was done via Zoom with
us in a Stanford recording studio.

Statistical
Learning MOOC with Rob Tibshirani. Updated January, 2022
with new modules for additional chapters in second edition of
Introduction to Statistical Learning. Includes new videotaped
interviews with David Cox, Geoff Hinton and Yoav Benjamini.
Hosted by edX in self-paced mode. See link for details of course and
certification.
Link
to Youtube
playlist for all 105 videos.

Introduction
to Statistical Learning, with applications in R (2nd
edition)
Published August 1, 2021. Available in eprint from
Springer.
Orders can be placed for hardcover, available August 30, 2021.
Three additional
chapters in additional 179 pages:
- Deep Learning
- Survival Analysis and Survival Data
- Multiple Testing
 glmnet 4.0 released May
2020 and on CRAN. Major addition is full GLM family functionality. Any legitimate
GLM family object can be passed as the family argument to glmnet, over and above
the built-in (and more computationally efficient) families which are
specified by character strings.
All the new features of glmnet 3.0 apply, including relaxed lasso and
elastic net, software for model assessment, functions for building
the X matrix that can deal
with NAs and factor inputs, a progress bar for fitting big models, and
more.

Computer Age Statistical Inference with Bradley Efron. Cambridge
University
Press, August
2016
Interview with the authors at the launch of the book in 2017 at
the Joint Statistical Meetings in Baltimore.

Interview with Jon Gurstelle for Statistics Views, November 2016

Statistical Learning with Sparsity with Martin Wainwright and
Rob Tibshirani.
Chapman and Hall, May 2015.
© copyright 2003 Trevor Hastie - All rights reserved.
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