High-dimensional statistics with R
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Updated
Apr 16, 2024 - HTML
High-dimensional statistics with R
An R package for assumption-lean covariance matrix estimation in high dimensions
Regularized estimation of high-dimensional FAVAR models
High Dimensional Portfolio Selection with Cardinality Constraints
Leveraging the full dimensionality of single-cell transcriptomics (among other things!)
Julia package to perform Bayesian clustering of high-dimensional Euclidean data using pairwise dissimilarity information.
Implementation of High-dimensional vector autoregression time series modeling via tensor decomposition, Di Wang, Yao Zheng, Heng Lian, Guodong Li. Written in JAX.
Code for the paper "Interpolation can hurt robust generalization even when there is no noise" available here: https://papers.nips.cc/paper/2021/hash/c4f2c88e16a579900657c18726641c81-Abstract.html
Official code repository for "Penalized MLE of multi-layer Gaussian Graphical Models"
Python scripts from paper Optimal cleaning for singular values of cross-covariance matrices, by Florent Benaych-Georges, Jean-Philippe Bouchaud, Marc Potters (see https://arxiv.org/abs/1901.05543)
Bayesian survival models for high-dimensional data
Fast and flexible models for extremal events.
High-dimensional Statistics in R, online workshop 27 Feb - 1 Mar
High-dimensional Statistics in R, online workshop 19 - 22 Mar
Accessible implementation of statistical learning algorithms, non-parametric and high-dimensional methods.
Thresholded Ordered Sparse CCA
On Storey’s direct approach to false discovery rates - High-Dimensional Data Analysis Seminar
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