Tag: High-Dimensional
- Asymptotic Properties of High-Dimensional Random Forests
- Bayesian Sparse Multiple Regression
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Cross-Validation for High-Dimensional Ridge and Lasso
This note collects several references on the research of cross-validation.
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Group Inference in High Dimensions
This post is based on the slides for the talk given by Zijian Guo at The International Statistical Conference In Memory of Professor Sik-Yum Lee
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Genetic Relatedness in High-Dimensional Linear Models
This post is based on Guo, Z., Wang, W., Cai, T. T., & Li, H. (2019). Optimal Estimation of Genetic Relatedness in High-Dimensional Linear Models. Journal of the American Statistical Association, 114(525), 358–369.
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Feature Annealed Independent Rules
This note is based on Fan, J., & Fan, Y. (2008). High-dimensional classification using features annealed independence rules. The Annals of Statistics, 36(6), 2605–2637.
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Sparse LDA
This note is based on Shao, J., Wang, Y., Deng, X., & Wang, S. (2011). Sparse linear discriminant analysis by thresholding for high dimensional data. The Annals of Statistics, 39(2), 1241–1265.
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Debiased Lasso
This post is based on Section 6.4 of Hastie, Trevor, Robert Tibshirani, and Martin Wainwright. “Statistical Learning with Sparsity,” 2016, 362.
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High-dimensional linear mixed-effect model
This post is based on Li, S., Cai, T. T., & Li, H. (2019). Inference for high-dimensional linear mixed-effects models: A quasi-likelihood approach. ArXiv:1907.06116 [Stat].
- High Dimensional Linear Discriminant Analysis
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Surprises in High-Dimensional Ridgeless Least Squares Interpolation
This post is based on Hastie, T., Montanari, A., Rosset, S., & Tibshirani, R. J. (2019). Surprises in High-Dimensional Ridgeless Least Squares Interpolation. 53.
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PLS in High-Dimensional Regression
This note is based on Cook, R. D., & Forzani, L. (2019). Partial least squares prediction in high-dimensional regression. The Annals of Statistics, 47(2), 884–908.