Simulation.R

#MonteCarlo Simulation

#loading area 
library("decisionSupport")
library(readr)


input_table <- read.csv2("input_estimates.csv", header = TRUE)
input_table

#Build function-decision_model###
decision_model <- function(x, varnames){
#area distribution

area_crop <- 0.8         #area for crops

area_row <- 1-area_crop  #area of the rows of pv or forest


#income factors

income_crop <- 
  crop_yield*crop_monetary
income_pv <-
  (income_crop * area_crop * yield_loss_pv) + (profit_pv * area_row * fluctuation_pv) + subsidies_pv
income_af <-
  ( income_crop * area_crop * yield_loss_af) 
  + (profit_af * area_row * fluctuation_af) + subsidies_af + ecosystem_service_af

#cost factors

cost_pv <- annual_cost_pv + investment_cost_pv 
cost_af <- harvesting_cost_af + annual_cost_af + investment_cost_af

#profits

profits_crop <- income_crop
profits_pv   <- income_pv - cost_pv
profits_af <- income_af - cost_af

return(profits_crop, profits_pv, profits_af) 
}

###from seminar 6
mcSimulation(estimate = as.estimate(input_table),
             model_function = decision_model,
             numberOfModelRuns = 100,
             functionSyntax = "plainNames")