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:
RTFA_0.1.0.tar.gz
RTFA_0.1.0.tar.gz(r-4.5-noble)RTFA_0.1.0.tar.gz(r-4.4-noble)
RTFA_0.1.0.tgz(r-4.4-emscripten)RTFA_0.1.0.tgz(r-4.3-emscripten)
RTFA.pdf |RTFA.html✨
RTFA/json (API)
# Install 'RTFA' in R: |
install.packages('RTFA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:0af62f2afa. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 22 2024 |
R-4.5-linux | OK | Dec 22 2024 |