T
Trevor Hastie
Researcher at Stanford University
Publications - 428
Citations - 230646
Trevor Hastie is an academic researcher from Stanford University. The author has contributed to research in topics: Lasso (statistics) & Feature selection. The author has an hindex of 124, co-authored 412 publications receiving 202592 citations. Previous affiliations of Trevor Hastie include University of Waterloo & University of Toronto.
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Book
Statistical Models in S
John M. Chambers,Trevor Hastie +1 more
TL;DR: The interactive data analysis and graphics language S has become a popular environment for both data analysts and research statisticians, but a common complaint has concerned the lack of statistical modeling tools, such as those provided by GLIM© or GENSTAT©.
BookDOI
Statistical Learning with Sparsity: The Lasso and Generalizations
TL;DR: Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data and extract useful and reproducible patterns from big datasets.
Journal ArticleDOI
Generalized linear and generalized additive models in studies of species distributions: setting the scene
TL;DR: A series of papers prepared within the framework of an international workshop entitled: Advances in GLMs /GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6 � /11 August 2001 are introduced.
Journal ArticleDOI
Pathwise coordinate optimization
TL;DR: It is shown that coordinate descent is very competitive with the well-known LARS procedure in large lasso problems, can deliver a path of solutions efficiently, and can be applied to many other convex statistical problems such as the garotte and elastic net.