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Generate and propagate Monte Carlo Simulations based on a template input file.

Source: R/fct_combine_mcs_E.R
fct_combine_mcs_E.Rd

TBD

Usage

fct_combine_mcs_E(.ad, .cs, .usr)

Arguments

.ad

Activity Data input table for the shiny app (AD_lu_transitions)

.cs

Carbon Stock input table for the shiny app (c_stocks)

.usr

User inputs' table for the shiny app (user_inputs). Contains the number of iterations of the MCS, carbon fraction if needed and if truncated PDFs should be used when necessary.

Value

A list of dataframes with Monte Carlo simulations for input variables, REDD+ activities CO2 emissions and removals and emission reductions levels.

Examples

library(readxl)
library(dplyr)
library(mocaredd)

cs <- read_xlsx(
  system.file("extdata/example1.xlsx", package = "mocaredd"),
  sheet = "c_stocks",
  na = "NA"
  )
ad <- read_xlsx(
  system.file("extdata/example1.xlsx", package = "mocaredd"),
  sheet = "AD_lu_transitions",
  na = "NA"
  )
usr <- read_xlsx(
  system.file("extdata/example1.xlsx", package = "mocaredd"),
  sheet = "user_inputs",
  na = "NA"
  )

cs_clean <- cs |> filter(!is.na(c_value) | !is.na(c_pdf_a))

res <- fct_combine_mcs_E(.ad = ad, .cs = cs_clean, .usr = usr)
#> Random simulations with seed: 93
hist(res$E_sim)

round(median(res$E_sim))
#> [1] 75830