Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation
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Updated
Oct 16, 2026 - Python
Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
Online Covariance and Correlation Estimation
Production multi-asset portfolio construction and rolling backtesting in Python
Lightweight robust covariance estimation in Julia
Implementation of linear CorEx and temporal CorEx.
Sparse multi-output factor-model estimation with sign constraints, prior-centered shrinkage, data-driven grouped penalties, and consistent factor covariance assembly
Portfolio optimisation library for Julia. Over 50 risk measures (CVaR, EVaR, RLVaR, drawdown, OWA), hierarchical risk parity, HERC, nested clustered optimisation, risk budgeting, near-optimal centering, four Black-Litterman variants, entropy pooling, factor and high-order priors, denoising, and JuMP-backed convex and non-convex optimization.
Mean and Covariance Matrix Estimation under Heavy Tails
R Package: Regularized Principal Component Analysis for Spatial Data
Implementation of the Paper "Channel Estimation for Quantized Systems based on Conditionally Gaussian Latent Models".
gips - Gaussian model Invariant by Permutation Symmetry
PCA, Factor Analysis, CCA, Sparse Covariance Matrix Estimation, Imputation, Multiple Hypothesis Testing
Framework for estimating parameters and the empirical sandwich covariance matrix from a set of unbiased estimating equations (i.e. M-estimation) in R.
Code for NeurIPS 2025 paper - Covariances for Free: Exploiting Mean Distributions for Training-free Federated Learning
Chronos-2 是一个用于时间序列预测的基础模型,基于 Chronos 和 Chronos-Bolt 构建。它提供了显著的能力改进,可以处理早期模型不支持的多种预测场景。支持的场景包括(1)单变量时间序列预测:经典的时间序列预测任务;(2)跨项目学习:利用多个相关时间序列的信息进行预;(3)多变量预测:同时预测多个相关目标变量(3)带协变量的预测:仅过去协变量:在预测时已知的历史协变量(如过去的天气数据) + 已知未来协变量:预测期间已知的协变量(如节假日、计划事件)
R code and dataset for the paper on spatially functional data
General purpose correlation and covariance estimation
Unidimensional trivial Kalman filter (header only, Arduino compatible) library
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