# Multivariate and 2D Extensions of Singular Spectrum Analysis with the Rssa Package

arXiv: https://arxiv.org/abs/1309.5050 · HTML: https://mlsanity.com/paper/1309.5050/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Sep 2013.

## Built on by (most cited first, 2 of 2)

- [Hankel low-rank approximation and completion in time series analysis and forecasting: a brief review](https://mlsanity.com/paper/2206.05103/) (2022)
- [Application of the Singular Spectrum Analysis on electroluminescence images of thin-film photovoltaic modules](https://mlsanity.com/paper/2109.04048/) (2021)

## Abstract (arXiv)

Implementation of multivariate and 2D extensions of Singular Spectrum Analysis (SSA) by means of the R-package Rssa is considered. The extensions include MSSA for simultaneous analysis and forecasting of several time series and 2D-SSA for analysis of digital images. A new extension of 2D-SSA analysis called Shaped 2D-SSA is introduced for analysis of images of arbitrary shape, not necessary rectangular. It is shown that implementation of Shaped 2D-SSA can serve as a base for implementation of MSSA and other generalizations. Efficient implementation of operations with Hankel and Hankel-block-Hankel matrices through FFT is suggested. Examples with code fragments in R, which explain the methodology and demonstrate the proper use of Rssa, are presented.