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: |
1.2.3 |
Depends: |
R (≥ 3.5.0) |
Imports: |
stats, MASS, graphics |
Suggests: |
zoo, knitr, WASP, NPRED, rmarkdown, testthat, devtools |
Published: |
2021-11-27 |
Author: |
Ze Jiang [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, TimeSeries |
CRAN checks: |
synthesis results |
Documentation:
Downloads:
Reverse dependencies:
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