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 Macherla ORCID iD [aut, cre]
Maintainer: Sidharth Macherla <msidharthrasik at>
License: MIT + file LICENSE
NeedsCompilation: no
Citation: conjurer citation info
Materials: NEWS
CRAN checks: conjurer results


Reference manual: conjurer.pdf
Vignettes: Industry Example
Introduction to conjurer


Package source: conjurer_1.7.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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