NTS: Nonlinear Time Series Analysis

Simulation, estimation, prediction procedure, and model identification methods for nonlinear time series analysis, including threshold autoregressive models, Markov-switching models, convolutional functional autoregressive models, nonlinearity tests, Kalman filters and various sequential Monte Carlo methods. More examples and details about this package can be found in the book "Nonlinear Time Series Analysis" by Ruey S. Tsay and Rong Chen, John Wiley & Sons, 2018 (ISBN: 978-1-119-26407-1).

Version: 1.1.3
Depends: R (≥ 3.6.0)
Imports: base, dlm, graphics, MASS, MSwM, Rdpack, parallel, splines, stats, tensor
Suggests: testthat
Published: 2023-09-24
DOI: 10.32614/CRAN.package.NTS
Author: Ruey Tsay [aut], Rong Chen [aut], Xialu Liu [aut, cre]
Maintainer: Xialu Liu <xialu.liu at sdsu.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
In views: TimeSeries
CRAN checks: NTS results


Reference manual: NTS.pdf


Package source: NTS_1.1.3.tar.gz
Windows binaries: r-devel: NTS_1.1.3.zip, r-release: NTS_1.1.3.zip, r-oldrel: NTS_1.1.3.zip
macOS binaries: r-release (arm64): NTS_1.1.3.tgz, r-oldrel (arm64): NTS_1.1.3.tgz, r-release (x86_64): NTS_1.1.3.tgz, r-oldrel (x86_64): NTS_1.1.3.tgz
Old sources: NTS archive


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