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synthesis

Synthetic data generator

https://github.com/zejiang-unsw/synthesis

Science Score: 26.0%

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    CITATION.cff file
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    .zenodo.json file
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    DOI references
    Found 3 DOI reference(s) in README
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    Scientific vocabulary similarity
    Low similarity (13.2%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Synthetic data generator

Basic Info
Statistics
  • Stars: 3
  • Watchers: 1
  • Forks: 1
  • Open Issues: 1
  • Releases: 5
Created over 6 years ago · Last pushed about 2 years ago
Metadata Files
Readme

README.md

synthesis: Synthetic data generator

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}.

It can be used for variable selection, prediction, and classification and clustering problem generation.

Requirements

Dependencies:
  stats, MASS

Suggest:
  testthat, devtools

Installation

You can install the package via devtools from GitHub with:

r devtools::install_github("zejiang-unsw/synthesis")

or via CRAN with:

r install.packages("synthesis")

Report issues

https://github.com/zejiang-unsw/synthesis/issues

Update history

synthesis 1.2.2

  • Included the affine error model.
  • Included the Brownian motion models.
  • Included the build-up and wash-off water quality model.
  • Updated the vignette.

synthesis 1.2.1

  • Added a vignette to the package.
  • Included the state-space model.

synthesis 1.2.0

  • Added a NEWS.md file to track changes to the package.
  • Initial version submitted to CRAN.

Citation

Jiang, Z., Rashid, M. M., Johnson, F., & Sharma, A. (2020). A wavelet-based tool to modulate variance in predictors: An application to predicting drought anomalies. Environmental modelling & software, 135, 104907.

Jiang, Z., Sharma, A., & Johnson, F. (2020). Refining Predictor Spectral Representation Using Wavelet Theory for Improved Natural System Modeling. Water Resources Research, 56(3), e2019WR026962.

Jiang, Z., Sharma, A., & Johnson, F. (2019). Assessing the sensitivity of hydro-climatological change detection methods to model uncertainty and bias. Advances in Water Resources, 134, 103430.

Galelli, S., Humphrey, G. B., Maier, H. R., Castelletti, A., Dandy, G. C., & Gibbs, M. S. (2014). An evaluation framework for input variable selection algorithms for environmental data-driven models. Environmental modelling & software, 62, 33-51.

Sharma, A. (2000). Seasonal to interannual rainfall probabilistic forecasts for improved water supply management: Part 1 - A strategy for system predictor identification. Journal of Hydrology, 239(1), 232-239.

Owner

  • Name: Ze Jiang
  • Login: zejiang-unsw
  • Kind: user
  • Location: Sydney, Australia
  • Company: UNSW

Postdoctoral Research Fellow in the School of Civil and Environmental Engineering's Water Research Centre (WRC) at University of NSW

GitHub Events

Total
Last Year

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 40
  • Total Committers: 1
  • Avg Commits per committer: 40.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
zejiang-unsw 4****w 40

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 2
  • Total pull requests: 0
  • Average time to close issues: 26 days
  • Average time to close pull requests: N/A
  • Total issue authors: 1
  • Total pull request authors: 0
  • Average comments per issue: 0.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • zejiang-unsw (2)
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 750 last-month
  • Total docker downloads: 41,971
  • Total dependent packages: 2
  • Total dependent repositories: 2
  • Total versions: 6
  • Total maintainers: 1
cran.r-project.org: synthesis

Generate Synthetic Data from Statistical Models

  • Versions: 6
  • Dependent Packages: 2
  • Dependent Repositories: 2
  • Downloads: 750 Last month
  • Docker Downloads: 41,971
Rankings
Dependent packages count: 13.3%
Downloads: 16.3%
Average: 19.3%
Dependent repos count: 19.6%
Forks count: 21.3%
Stargazers count: 25.8%
Maintainers (1)
ze.jiang@unsw.edu.au
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
  • MASS * imports
  • graphics * imports
  • stats * imports
  • NPRED * suggests
  • WASP * suggests
  • devtools * suggests
  • knitr * suggests
  • rmarkdown * suggests
  • testthat * suggests
  • zoo * suggests