Quick info
Trevor Hastie has worked on 26 packages so far. In total, Trevor Hastie has worked with 55 other authors on those packages. Impressive teamwork!
Packages overview
Package details
| FLLat | Fused Lasso Latent Feature Model Gen Nowak , Trevor Hastie , Jonathan R. Pollack , Robert Tibshirani , Nicholas Johnson |
| ISLR | Data for an Introduction to Statistical Learning with Applications in R Gareth James , Daniela Witten , Trevor Hastie , Rob Tibshirani |
| ISLR2 | Introduction to Statistical Learning, Second Edition Gareth James , Daniela Witten , Trevor Hastie , Rob Tibshirani , Balasubramanian Narasimhan |
| ProDenICA | Product Density Estimation for ICA using Tilted Gaussian Density Estimates Trevor Hastie , Rob Tibshirani |
| SGL | Fit a GLM (or Cox Model) with a Combination of Lasso and Group Lasso Regularization Noah Simon , Jerome Friedman , Trevor Hastie , Rob Tibshirani |
| SLOPE | Sorted L1 Penalized Estimation Johan Larsson , Jonas Wallin , Malgorzata Bogdan , Ewout van den Berg , Chiara Sabatti , Emmanuel Candes , Evan Patterson , Weijie Su , Jakub Kała , Krystyna Grzesiak , Michal Burdukiewicz , Jerome Friedman , Trevor Hastie , Rob Tibshirani , Balasubramanian Narasimhan , Noah Simon , Junyang Qian , Akarsh Goyal |
| TrioSGL | Trio Model with a Combination of Lasso and Group Lasso Regularization Timo Stöcker , Noah Simon , Jerome Friedman , Trevor Hastie , Rob Tibshirani |
| customizedTraining | Customized Training for Lasso and Elastic-Net Regularized Generalized Linear Models Scott Powers , Trevor Hastie , Robert Tibshirani |
| elasticnet | Elastic-Net for Sparse Estimation and Sparse PCA |
| gam | Generalized Additive Models |
| gamsel | Fit Regularization Path for Generalized Additive Models Alexandra Chouldechova , Trevor Hastie , Balasubramanian Narasimhan , Vitalie Spinu |
| glasso | Graphical Lasso Jerome Friedman , Trevor Hastie , Rob Tibshirani |
| glinternet | Learning Interactions via Hierarchical Group-Lasso Regularization |
| glmnet | Lasso and Elastic-Net Regularized Generalized Linear Models Jerome Friedman , Trevor Hastie , Rob Tibshirani , Balasubramanian Narasimhan , Kenneth Tay , Noah Simon , Junyang Qian , James Yang |
| glmpath | L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model Mee Young Park , Trevor Hastie |
| lars | Least Angle Regression, Lasso and Forward Stagewise |
| multiview | Cooperative Learning for Multi-View Analysis Daisy Yi Ding , Robert J. Tibshirani , Balasubramanian Narasimhan , Trevor Hastie , Kenneth Tay , James Yang |
| npmr | Nuclear Penalized Multinomial Regression Scott Powers , Trevor Hastie , Robert Tibshirani |
| pcoxtime | Penalized Cox Proportional Hazard Model for Time-Dependent Covariates Bicko Cygu , Ben Bolker , Trevor Hastie |
| princurve | Fit a Principal Curve in Arbitrary Dimension Trevor Hastie , Andreas Weingessel , Kurt Hornik , Henrik Bengtsson , Robrecht Cannoodt |
| rda | Shrunken Centroids Regularized Discriminant Analysis Yaqian Guo , Trevor Hastie , Robert Tibshirani , Valentin Todorov |
| softImpute | Matrix Completion via Iterative Soft-Thresholded SVD Trevor Hastie , Rahul Mazumder |
| sparsegl | Sparse Group Lasso Daniel J. McDonald , Xiaoxuan Liang , Anibal Solón Heinsfeld , Aaron Cohen , Yi Yang , Hui Zou , Jerome Friedman , Trevor Hastie , Rob Tibshirani , Balasubramanian Narasimhan , Kenneth Tay , Noah Simon , Junyang Qian , James Yang |
| stepPlr | L2 Penalized Logistic Regression with Stepwise Variable Selection Mee Young Park , Trevor Hastie |
| svmpath | The SVM Path Algorithm |
| tf | S3 Classes and Methods for Tidy Functional Data Fabian Scheipl , Jeff Goldsmith , Julia Wrobel , Maximilian Muecke , Sebastian Fischer , Trevor Hastie , Rahul Mazumder , Chen Meng |