synthesis: Generate Synthetic Data from Statistical Models

Generate synthetic time series from commonly used statistical models, including linear, nonlinear and chaotic systems. Applications to testing methods can be found in Jiang, Z., Sharma, A., & Johnson, F. (2019) <doi:10.1016/j.advwatres.2019.103430> and Jiang, Z., Sharma, A., & Johnson, F. (2020) <doi:10.1029/2019WR026962> associated with an open-source tool by Jiang, Z., Rashid, M. M., Johnson, F., & Sharma, A. (2020) <doi:10.1016/j.envsoft.2020.104907>.

Version: 1.2.1
Depends: R (≥ 3.5.0)
Imports: stats, MASS, graphics
Suggests: testthat, devtools, knitr, rmarkdown, zoo
Published: 2021-04-02
Author: Ze Jiang ORCID iD [aut, cre]
Maintainer: Ze Jiang <ze.jiang at unsw.edu.au>
BugReports: https://github.com/zejiang-unsw/synthesis/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/zejiang-unsw/synthesis#readme
NeedsCompilation: no
Materials: README NEWS
In views: Hydrology
CRAN checks: synthesis results

Downloads:

Reference manual: synthesis.pdf
Vignettes: synthesis
Package source: synthesis_1.2.1.tar.gz
Windows binaries: r-devel: synthesis_1.2.1.zip, r-release: synthesis_1.2.1.zip, r-oldrel: synthesis_1.2.1.zip
macOS binaries: r-release: synthesis_1.2.1.tgz, r-oldrel: synthesis_1.2.1.tgz
Old sources: synthesis archive

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