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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 Division of Biostatistics of the Health, Research and Policy Department 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. For more
details, click on the link to my biography.
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Introduction
to Statistical Learning, with applications in R (2nd
edition)
In press, and to appear soon in 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.

Statistical
Learning MOOC with Rob Tibshirani. January, 2020. Now hosted by edX in self-paced mode. See link for details of course and certification.

Interview with Jon Gurstelle for Statistics Views, November 2016
 glmnet in python ported by BJ Balakumar
October 2016

Computer Age Statistical Inference with Bradley Efron. Cambridge University Press, August 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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