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CDSimX  

Simulating Climate Data for Research and Modelling
View on CRAN: Click here


Download and install CDSimX package within the R console
Install from CRAN:
install.packages("CDSimX")

Install from Github:
library("remotes")
install_github("cran/CDSimX")

Install by package version:
library("remotes")
install_version("CDSimX", "1.1.2")



Attach the package and use:
library("CDSimX")
Maintained by
Isaac Osei
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-10
Latest Update: 2026-07-10
Description:
Advanced climate simulation, forecasting, visualization, export, and machine learning tools. Generates synthetic climate datasets for single or multiple weather stations using stochastic weather generation techniques. 'CDSimX' simulates daily climate variables including minimum and maximum temperature, rainfall, relative humidity, solar radiation, wind speed, wind direction, dew point temperature, and potential evapotranspiration. The package incorporates seasonal harmonic models, Markov chain rainfall occurrence processes, Gamma-distributed rainfall amounts, copula-based dependence structures, bias-correction procedures, and physical consistency constraints. 'CDSimX' supports climate data generation, environmental modeling, machine learning benchmarking, sensitivity analysis, and educational applications. Methods are based on established stochastic weather generation approaches described in Richardson (1981) <doi:10.1029/WR017i001p00182>, Wilks (1999) <doi:10.1016/S0168-1923(99)00037-4>, and Osei et al. (2026) <doi:10.5334/jors.666>.
How to cite:
Isaac Osei (2026). CDSimX: Simulating Climate Data for Research and Modelling. R package version 1.1.2, https://cran.r-project.org/web/packages/CDSimX. Accessed 20 Oct. 2026.
Previous versions and publish date:
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Complete documentation for CDSimX
Functions, R codes and Examples using the CDSimX R package
Full CDSimX package functions and examples
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