#An introduction to statistical learning [df how to
We show how to use GLMs to fit community models, which are traditionally fit by maximum entropy. CATS regression - a model-based approach to studying trait-based community assembly.
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Confidence Intervals for Random Forests: the Jackknife and the Infinitessimal Jackknife. Stefan Wager, Trevor Hastie and Bradley Efron.In this survey across the more than 1,600 traits in the UK Biobank, we report 428 strongly significant (pp in forward stepwise. Significant Sparse Polygenic Risk Scores across 428 traits in UK Biobank. Yosuke Tanigawa, Junyang Qian, Guhan Venkataraman, Johanne Justesen, Ruilin Li, Robert Tibshirani, Trevor Hastie, Manuel Rivas. In this paper we extend the method to conditional density estimation via trees and then gradient boosting with trees. In particular, we represent an exponential tilt function in a basis of natural splines, and use discretization to deal with the normalization. Lindsey's method allows for smooth density estimation by turning the density problem into a Poisson GLM. LinCDE: Conditional density estimation via Lindsey's method.
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We show how to scale these algorithms to high-dimensional problems. We consider two acceleration schemes, Nesterov and Anderson, and discuss their implementation.
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We develop algorithms for computing an element-weighted low-rank matrix approximation (SVD) via projected gradient descent. National Science Foundation and the National Institutes of Health. The research reported here was partially supported by grants from the Statistical Learning with Sparsity: the Lasso and Generalizationsīy Trevor Hastie, Robert Tibshirani and Martin Wainwright (May 2015)ĭata Mining, Inference, and Prediction (Second Edition)īy Trevor Hastie, Robert Tibshirani and Jerome Friedman (2009)Īn Introduction to Statistical Learning with Applications in Rīy Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani (June 2013)īy Trevor Hastie, Robert Tibshirani and Jerome Friedman (2001)Įdited by John Chambers and Trevor Hastie (1991)īy Trevor Hastie and Robert Tibshirani (1990) An Introduction to Statistical Learning with Applications in R (second edition)īy Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani (August 2021)ģ new chapters (+179 pages), including Deep LearningĬomputer Age Statistical Inference:Algorithms, Evidence and Data Scienceīy Bradley Efron and Trevor Hastie (August 2016)