This package is the R version of the DIETCOST SOFTWARE, providing tools to easily perform Monte Carlo simulations, aiming to evaluate the cost and environmental impact of a diet. Also provided are tools to manipulate the data and to conduct basic statistical analysis of the results.
You can install the stable version of DIETCOST from CRAN with:
install.packages("DIETCOST")
Also, the development version of DIETCOST is available in GitHub:
# install.packages("devtools")
# devtools::install_github("hbracarense/dietcost")
install.packages("DIETCOST", repos = c('https://hbracarense.r-universe.dev', 'https://cloud.r-project.org'))
The main function of this package is monteCarloSimulation(), displayed bellow:
library(DIETCOST)
monteCarloSimulation(tempdir(), 5, DIETCOST::foods, DIETCOST::nutrient_targets, DIETCOST::food_groups, person = 'woman', 'PF', c(1,2,3), 0.5, allow_discretionary = TRUE, allow_alcohol = TRUE, allow_takeaway = TRUE)
This function saves in the top directory a report containing the stats of the run. It also creates a folder, which will store the resulting diets, if any is formed, as a .csv.
The development of this package also encompassed the creation of a ‘standard table’, whose use is greatly advised to ensure better results. Although the usage of this package is possible with different dataset formats, choosing to adopt the ‘standard table’ makes DIETCOST so much easier.
This table is made availabe throught the GitHub repo and also as .xlsx on the external data folder of the package. Said folder also houses two script examples.
Finally, this package also contains the already preprocessed datased, which can be accessed and stored into R dataframes as bellow:
foods_df <- DIETCOST::foods
food_groups_df <- DIETCOST::food_groups
nutrient_targets <- DIETCOST::nutrient_targets
Please report any bugs or submit any queries either to this GitHub repo or to h@bracarense.com.