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.
Papers
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Penalized logistic regression for detecting gene interactions
Mee Young Park,Trevor Hastie +1 more
TL;DR: This work proposes using a variant of logistic regression with (L)_(2)-regularization to fit gene-gene and gene-environment interaction models and demonstrates that this method outperforms other methods in the identification of the interaction structures as well as prediction accuracy.
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Comparative performance of generalized additive models and multivariate adaptive regression splines for statistical modelling of species distributions
TL;DR: In this paper, two statistical modelling techniques, generalized additive models (GAM) and multivariate adaptive regression splines (MARS), were used to analyse relationships between the distributions of 15 freshwater fish species and their environment.
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Classification of gene microarrays by penalized logistic regression
Ji Zhu,Trevor Hastie +1 more
TL;DR: In this paper, the authors proposed penalized logistic regression (PLR) as an alternative to the SVM for the microarray cancer diagnosis problem and showed that when using the same set of genes, PLR and SVM perform similarly in cancer classification, but PLR has the advantage of additionally providing an estimate of the underlying probability.
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Generalized additive models for medical research
Trevor Hastie,Robert Tibshirani +1 more
TL;DR: Flexible statistical methods that are useful for characterizing the effect of potential prognostic factors on disease endpoints are reviewed.
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Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort.
Anna Shcherbina,C. Mikael Mattsson,Daryl Waggott,Heidi Salisbury,Jeffrey W. Christle,Trevor Hastie,Matthew T. Wheeler,Euan A. Ashley +7 more
TL;DR: Most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs.