Factor-Adjusted Network Estimation and Forecasting for High-Dimensional Time Series
Overview
Implements methods for network estimation and forecasting of high-dimensional time series exhibiting strong serial and cross-sectional correlations under a factor-adjusted vector autoregressive model. See Barigozzi, Cho and Owens (2024+) doi:10.1080/07350015.2023.2257270 for further descriptions of FNETS methodology and Owens, Cho and Barigozzi (2024+) arXiv:2301.11675 accompanying the R package.
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Haeran Cho <haeran.cho@bristol.ac.uk>’ The Description field contains methodology and Owens, Cho and Barigozzi (2024+) <arXiv:2301.11675> Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
- NOTE11 OK, 2 NOTENow
- NOTE12 OK, 2 NOTE2026-03-10
Documentation
- Help pages
- 40 (18 internal)
- Examples that run
- 48%10 run in a plain check · 6 only when donttest examples are enabled (R CMD check --as-cran) · 5 never run
- Exported functions with examples
- 90%
- Documented parameters
- 85%
- Return-value docs
- 90%
- Help pages citing references
- 35%
Downloads
Dependencies
Installing fnets adds 20 packages (12 with compiled code, 21 MB of source tarballs). Heaviest: igraph 4.8 MB, fields 3.9 MB, spam 3.1 MB.
Code & Tests
Datasets
People & History
Package metadata
- First published
- 2023-01-26
- Total releases
- 6 / 3 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 4.1.0
- Bundled data
- 380 KB / 2 files
- Download size
- 424 KB
Cite
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