Supplementary_Ruett_Precision_Agriculture

This repository contains files that contribute to our supplementary materials of the Manuscript: 'Assessing expected utility and profitability to support decision-making for disease control strategies in ornamental heather production' by Marius Ruett, Tobias Dalhaus, Cory Whitney, and Eike Luedeling (under review 2021) (The DOI of the Manuscript can be found here when published). Within this repository we provide all necessary files to comprehend procedure of code calculations. We illustrate our code for data visualization that enables reproductivity of our figures. Code chunks can be used or optimized for own illustrations based on decisionSupport outcomes.

File descriptions

The Input Table

Our input table Input_CBA.csv contains all expert estimates that are used in our Simulation and Cost_Benefit function.

The Legend File

Our legend file Legend_CBA.csv contains all variable descriptions that we use in our code.

The Model

Model_Script.R and Simulation_Function.R contain our full code to run the model.

The Expected Utility Analysis

Expected_Utility_Analysis.R contains our full code to run the expected utility analysis.

The Code to create Figures

Plotting_the_results.R contains our full code to create the figures.

The R project

Supplementary_Ruett_Precision_Agriculture.Rproj is where we stored our R project.

The RMarkdown file

RMarkdown.Rmd contains our RMarkdown file as basis of our Supplementary materials.

The html file

Our RMarkdown file R_Markdown.Rmd generates the html file R_Markdown.html that represents our Supplementary materials.

Bibfile and citation style

We apply precision-agriculture.csl as a citation style for our Manuscript and Supplementary materials. All citations are stored in the biblibrary.bib file.

Folder descriptions

MC_Results_CBA

In this folder you find the results generated by the Monte Carlo simulation.

EVPI_Results_CBA

In this folder you find the results generated by the EVPI analysis.

Plots

In this folder you find our generated plots.