Distributed Online Covariance Matrix Tests
Two-Sample Covariance Test by Cai, Liu and Xia (2013)
One-Sample Covariance Test by Cai and Ma (2013)
Two-Sample Covariance Test by Cai and Ma (2013)
Two-Sample Covariance Test by Li and Chen (2012)
Two-Sample Covariance Test by Yu, Li and Xue (2022)
Two-Sample Covariance Test by Yu, Li, Xue and Li(2022)
Two-Sample Covariance Test by Yu, Li and Xue (2022)
One-Sample Covariance Test by Srivastava, Yanagihara, and Kubokawa (20...
Distributed Online Covariance Matrix Tests 'Docovt' is a powerful tool designed to efficiently process and analyze distributed datasets. It enables users to perform covariance matrix tests in an online, distributed manner, making it highly suitable for large-scale data analysis. By leveraging advanced computational techniques, 'Docovt' ensures robust and scalable solutions for statistical analysis, particularly in scenarios where data is dispersed across multiple nodes or sources. This package is ideal for researchers and practitioners working with high-dimensional data, providing a flexible and efficient framework for covariance matrix estimation and hypothesis testing. The philosophy of 'Docovt' is described in Guo G.(2025) <doi:10.1016/j.physa.2024.130308>.