modgo: Mock Data Generation
Generation of synthetic data from a real dataset using the combination of rank normal inverse transformation with the calculation of correlation matrix <doi:10.1055/a-2048-7692>. Completely artificial data may be generated through the use of Generalized Lambda Distribution and Generalized Poisson Distribution <doi:10.1201/9781420038040>. Quantitative, binary, ordinal categorical, and survival data may be simulated. Functionalities are offered to generate synthetic data sets according to user's needs.
| Version: |
1.0.1 |
| Depends: |
R (≥ 4.1) |
| Imports: |
ggplot2 (≥ 3.4.0), patchwork (≥ 1.1.2), wesanderson (≥
0.3.6.9000), Matrix (≥ 1.6.1.1), ggcorrplot (≥ 0.1.4.1), gridExtra (≥ 2.3), psych (≥ 2.2.9), GLDEX (≥ 2.0.0.9.2), MASS (≥ 7.3), gp (≥ 1.0), stats, utils, survival |
| Suggests: |
knitr, rmarkdown |
| Published: |
2024-09-11 |
| DOI: |
10.32614/CRAN.package.modgo |
| Author: |
Andreas Ziegler [aut],
Francisco Miguel Echevarria [aut],
Georgios Koliopanos [cre] |
| Maintainer: |
Georgios Koliopanos <george.koliopanos at cardio-care.ch> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Citation: |
modgo citation info |
| Materials: |
README |
| CRAN checks: |
modgo results |
Documentation:
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