robts-package: Robust Time Series Analysis
In robts: Robust Time Series Analysis

Description Details Author(s) References

Collection of R functions for robust time series analysis. This includes various approaches for robust estimation of (partial) autocorrelation, robust filtering, robust fitting of AR(p) processes as well as robust change point detection.

See the main functions acfrob for robust estimation of the autocorrelation function, arrob for robust fitting of autoregressive (AR) models, spectrumrob for robust estimation of the spectral density and changerob for robust change point tests.

Alexander Dürre, Tobias Liboschik, Jonathan Rathjens and Roland Fried

Maintainer: Alexander Dürre <alexander.duerre@tu-dortmund.de>

Dürre, A., Fried, R. and Liboschik, T. (2015): Robust estimation of (partial) autocorrelation, Wiley Interdisciplinary Reviews: Computational Statistics, vol. 7, 205–222, doi: 10.1002/wics.1351.

Maronna, R. A., Martin, R. D., and Yohai, V. J. (2006): Robust Statistics: Theory and Methods, Wiley, chapter 8, doi: 10.1002/0470010940.

robts documentation built on May 2, 2019, 4:55 p.m.