sufficientForecasting: Sufficient Forecasting using Factor Models

The sufficient forecasting (SF) method is implemented by this package for a single time series forecasting using many predictors and a possibly nonlinear forecasting function. Assuming that the predictors are driven by some latent factors, the SF first conducts factor analysis and then performs sufficient dimension reduction on the estimated factors to derive predictive indices for forecasting. The package implements several dimension reduction approaches, including principal components (PC), sliced inverse regression (SIR), and directional regression (DR). Methods for dimension reduction are as described in: Fan, J., Xue, L. and Yao, J. (2017) <doi:10.1016/j.jeconom.2017.08.009>, Luo, W., Xue, L., Yao, J. and Yu, X. (2022) <doi:10.1093/biomet/asab037> and Yu, X., Yao, J. and Xue, L. (2022) <doi:10.1080/07350015.2020.1813589>.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: gam, stats
Suggests: knitr, rmarkdown
Published: 2023-02-17
Author: Jianqing Fan [aut], Jing Fu [aut, cre], Wei Luo [aut], Lingzhou Xue [aut], Jiawei Yao [aut], Xiufan Yu [aut]
Maintainer: Jing Fu <jingfu991224 at>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
In views: TimeSeries
CRAN checks: sufficientForecasting results


Reference manual: sufficientForecasting.pdf
Vignettes: SF_vignette


Package source: sufficientForecasting_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): sufficientForecasting_0.1.0.tgz, r-oldrel (arm64): sufficientForecasting_0.1.0.tgz, r-release (x86_64): sufficientForecasting_0.1.0.tgz, r-oldrel (x86_64): sufficientForecasting_0.1.0.tgz


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