fbi: Factor-Based Imputation for Missing Data

The codes in the fbi package are developed based on the following papers:

• Bai, Jushan and Ng, Serena (2021), "Matrix Completion, Counterfactuals, and Factor Analysis of Missing Data".

• Cahan, E., Bai, J. and Ng, S. (2021), "Factor-Based Imputation of Missing Values and Covariances in Panel Data of Large Dimensions".

• Bai, Jushan and Ng, Serena (2002), "Determining the number of factors in approximate factor models".

• Bai, Jushan and Ng, Serena (2019), "Rank regularized estimation of approximate factor models".

• McCracken, Michael W. and Ng, Serena (2015), "FRED-MD and FRED-QD: Monthly and Quarterly Databases for Macroeconomic Research".

Requirements

The fbi package requires the following three R packages:

• stats
• readr
• pracma

They should be installed prior to the installation of the fbi package:

install.packages("stats")
install.packages("readr")
install.packages("pracma")

Installation

The fbi package can be installed from github:

devtools::install_github("cykbennie/fbi")

Reference Manual

Refer to the fbi.pdf file for details.

Vignette

Download factor_fred.html for an example using the FRED-MD dataset (https://research.stlouisfed.org/econ/mccracken/fred-databases/).

Author

• Yankang (Bennie) Chen (cykbennie@outlook.com)

License

This project is licensed under the GNU General Public License v3.0 License - see the LICENSE file for details.

Acknowledgments

• Serena Ng (serena.ng@columbia.edu)
• Jushan Bai (jushan.bai@columbia.edu)