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, Wiley, 2018 (ISBN: 978-1-119-26407-1).

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: base, dlm, graphics, MASS, MSwM, Rdpack, parallel, splines, stats, tensor
Published: 2018-12-09
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

Downloads:

Reference manual: NTS.pdf
Package source: NTS_1.0.0.tar.gz
Windows binaries: r-devel: NTS_1.0.0.zip, r-release: NTS_1.0.0.zip, r-oldrel: NTS_1.0.0.zip
OS X binaries: r-release: NTS_1.0.0.tgz, r-oldrel: NTS_1.0.0.tgz

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