Rfssa: An R Package for Functional Singular Spectrum Analysis
Functional Singular Spectrum Analysis (FSSA) is a non-parametric approach for analyzing Functional Time Series (FTS) and Multivariate FTS (MFTS) data. This paper introduces Rfssa, an R package that addresses implementing FSSA for FTS and MFTS data types. Rfssa provides a flexible container, the funts class, for FTS/MFTS data observed on one-dimensional or multi-dimensional domains. It accepts arbitrary basis systems and offers powerful graphical tools for visualizing time-varying features and pattern changes. The package incorporates two forecasting algorithms for FTS data. Developed using object-oriented programming and Rcpp/RcppArmadillo, Rfssa ensures computational efficiency. The paper covers theoretical background, technical details, usage examples, and highlights potential applications of Rfssa.
Authors
- Mehdi Maadooliat (ORCID: https://orcid.org/0000-0002-5408-2676)
- Jordan Trinka (ORCID: https://orcid.org/0000-0001-9118-5781)
- Hossein Haghbin (ORCID: https://orcid.org/0000-0001-8947-287X)
Institutions
- Marquette University (US)
- Artificial Intelligence Research Institute (ES)
Publication Details
- Journal
- The R Journal
- Published
- 2025-03-11
- DOI
- https://doi.org/10.32614/rj-2024-019
- Primary Topic
- Statistical and numerical algorithms
- Type
- article
- Field-Weighted Citation Impact
- 0.00