HDTSA

An implementation for high-dimensional time series analysis methods, including factor model for vector time series proposed by Lam and Yao (2012) doi:10.1214/12-AOS970 and Chang, Guo and Yao (2015) doi:10.1016/j.jeconom.2015.03.024, martingale difference test proposed by Chang, Jiang and Shao (2023) doi:10.1016/j.jeconom.2022.09.001, principal component analysis for vector time series proposed by Chang, Guo and Yao (2018) doi:10.1214/17-AOS1613, cointegration analysis proposed by Zhang, Robinson and Yao (2019) doi:10.1080/01621459.2018.1458620, unit root test proposed by Chang, Cheng and Yao (2022) doi:10.1093/biomet/asab034, white noise test proposed by Chang, Yao and Zhou (2017) doi:10.1093/biomet/asw066, CP-decomposition for matrix time series proposed by Chang et al. (2023) doi:10.1093/jrsssb/qkac011 and Chang et al. (2024) doi:10.48550/arXiv.2410.05634, and statistical inference for spectral density matrix proposed by Chang et al. (2022) doi:10.48550/arXiv.2212.13686.

Last 30 days

This package has been downloaded 599 times in the last 30 days. More downloads than an obscure whitepaper, but not enough to bring down any servers. A solid effort! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 17 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 5,299 times in the last 365 days. A solid achievement! Enough downloads to get noticed at department meetings. The day with the most downloads was Jan 30, 2025 with 76 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.