Package: RTFA 0.1.0

Lingxiao Li

RTFA: Robust Factor Analysis for Tensor Time Series

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) <arxiv:2206.09800>, and Barigozzi et al. (2023) <arxiv:2303.18163>.

Authors:Matteo Barigozzi [aut], Yong He [aut], Lorenzo Trapani [aut], Lingxiao Li [aut, cre]

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Last updated 1 years agofrom:0af62f2afa. Checks:OK: 2. Indexed: yes.

Exports:TFM_estTFM_FN

Dependencies:rTensortensor