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conjurer: A Parametric Method for Generating Synthetic Data

Generates synthetic data distributions to enable testing various modelling techniques in ways that real data does not allow. Noise can be added in a controlled manner such that the data seems real. This methodology is generic and therefore benefits both the academic and industrial research.

Version:1.7.1
Depends:R (≥ 2.10)
Imports:jsonlite (≥ 1.8.0),httr (≥ 1.4.2), methods
Suggests:knitr,rmarkdown
Published:2023-01-18
DOI:10.32614/CRAN.package.conjurer
Author:Sidharth MacherlaORCID iD [aut, cre]
Maintainer:Sidharth Macherla <msidharthrasik at gmail.com>
BugReports:https://github.com/SidharthMacherla/conjurer/issues
License:MIT + fileLICENSE
URL:https://www.foyi.co.nz/posts/documentation/documentationconjurer/
NeedsCompilation:no
Citation:conjurer citation info
Materials:NEWS
CRAN checks:conjurer results

Documentation:

Reference manual:conjurer.html ,conjurer.pdf
Vignettes:Industry Example (source,R code)
Introduction to conjurer (source,R code)

Downloads:

Package source: conjurer_1.7.1.tar.gz
Windows binaries: r-devel:conjurer_1.7.1.zip, r-release:conjurer_1.7.1.zip, r-oldrel:conjurer_1.7.1.zip
macOS binaries: r-release (arm64):conjurer_1.7.1.tgz, r-oldrel (arm64):conjurer_1.7.1.tgz, r-release (x86_64):conjurer_1.7.1.tgz, r-oldrel (x86_64):conjurer_1.7.1.tgz
Old sources: conjurer archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=conjurerto link to this page.


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