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RTFA  

Robust Factor Analysis for Tensor Time Series
View on CRAN: Click here


Download and install RTFA package within the R console
Install from CRAN:
install.packages("RTFA")

Install from Github:
library("remotes")
install_github("cran/RTFA")

Install by package version:
library("remotes")
install_version("RTFA", "0.1.0")



Attach the package and use:
library("RTFA")
Maintained by
Lingxiao Li
[Scholar Profile | Author Map]
First Published: 2023-04-10
Latest Update: 2023-04-10
Description:
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) , and Barigozzi et al. (2023) .
How to cite:
Lingxiao Li (2023). RTFA: Robust Factor Analysis for Tensor Time Series. R package version 0.1.0, https://cran.r-project.org/web/packages/RTFA. Accessed 24 Feb. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited RTFA R package
View RTFA citation profile
Other R packages that RTFA depends, imports, suggests or enhances
Complete documentation for RTFA
Functions, R codes and Examples using the RTFA R package
Full RTFA package functions and examples
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