RTFA

Tensor Factor Models (TFM) are appealing dimension reduction tools for high-order tensor time series, and have wide applications in economics, finance and medical imaging. We propose an one-step projection estimator by minimizing the least-square loss function, and further propose a robust estimator with an iterative weighted projection technique by utilizing the Huber loss function. The methods are discussed in Barigozzi et al. (2022) doi:10.48550/arXiv.2206.09800, and Barigozzi et al. (2023) doi:10.48550/arXiv.2303.18163.

Last 30 days

This package has been downloaded 254 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 14 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 3,897 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Jan 30, 2025 with 36 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.