7models_20years.R

# Script to run models on 20 year data

# Source model formulas

source('final_models.R')
library(data.table)

# Set seed
set.seed(76568)

# Run standard Negative Binomial model
#########################################################################

# 20 - YEARS
# Results for 20 year - 1.5
twenty_year1.5 <- list.files(path = "./simulated_data/d20year/theta_1.5",
                             # Identify all csv files in folder
                             pattern = "*.csv", full.names = TRUE) %>% 
  lapply(fread) %>%             # Store all files in list
  map(negbinner) 
twenty_year1.5 <- do.call(rbind, twenty_year1.5)        # Combine data sets into one data set 
# check the data
head(twenty_year1.5)  
# write.csv
write.csv(twenty_year1.5, "./model_results/twenty_year_1.5_metrics.csv")
#______________________________________________________________________

# Results for 20 year - 5
twenty_year5 <- list.files(path = "./simulated_data/d20year/theta_5",
                           # Identify all csv files in folder
                           pattern = "*.csv", full.names = TRUE) %>% 
  lapply(fread) %>%             # Store all files in list
  map(negbinner) 
twenty_year5 <- do.call(rbind, twenty_year5)        # Combine data sets into one data set 
# check the data
head(twenty_year5)  
# write.csv
write.csv(twenty_year5, "./model_results/twenty_year_5_metrics.csv")

#______________________________________________________________________

# Results for 20 year - 10
twenty_year10 <- list.files(path = "./simulated_data/d20year/theta_10",
                            # Identify all csv files in folder
                            pattern = "*.csv", full.names = TRUE) %>% 
  lapply(fread) %>%           # Store all files in list
  map(negbinner) 
twenty_year10 <- do.call(rbind, twenty_year10)        # Combine data sets into one data set 
# check the data
head(twenty_year10)  
# write.csv
write.csv(twenty_year10, "./model_results/twenty_year_10_metrics.csv")

#______________________________________________________________________

# Results for 20 year - 100
twenty_year100 <- list.files(path = "./simulated_data/d20year/theta_100",
                             # Identify all csv files in folder
                             pattern = "*.csv", full.names = TRUE) %>% 
  lapply(fread) %>%              # Store all files in list
  map(negbinner) 
twenty_year100 <- do.call(rbind, twenty_year100)        # Combine data sets into one data set 
# check the data
head(twenty_year100)  
# write.csv
write.csv(twenty_year100, "./model_results/twenty_year_100_metrics.csv")

###############################################################

##### BAYESIAN MODEL

# Run Bayesian Negative Binomial model
#########################################################################
# Results for 20 year - 1.5
twenty_year1.5b <- list.files(path = "./simulated_data/d20year/theta_1.5",
                            # Identify all csv files in folder
                            pattern = "*.csv", full.names = TRUE) %>% 
  # Use fread from data.table to read in the files and store them in a list
  lapply(fread) %>%  
  # Use parLapply from parallel to apply stanbinner to each dataset in parallel
  parLapply(cl = cl, fun = stanbinner) 
twenty_year1.5b <- do.call(rbind, twenty_year1.5b)        # Combine data sets into one data set 
# check the data
head(twenty_year1.5b)  
# write.csv
write.csv(twenty_year1.5b, "./model_results/twenty_year_1.5b_metrics.csv")
#______________________________________________________________________

# Results for 20 year - 5
twenty_year5b <- list.files(path = "./simulated_data/d20year/theta_5",
                          # Identify all csv files in folder
                          pattern = "*.csv", full.names = TRUE) %>% 
  # Use fread from data.table to read in the files and store them in a list
  lapply(fread) %>%  
  # Use parLapply from parallel to apply stanbinner to each dataset in parallel
  parLapply(cl = cl, fun = stanbinner) 
twenty_year5b <- do.call(rbind, twenty_year5b)        # Combine data sets into one data set 
# check the data
head(twenty_year5b)  
# write.csv
write.csv(twenty_year5b, "./model_results/twenty_year_5b_metrics.csv")

#______________________________________________________________________

# Results for 20 year - 10
twenty_year10b <- list.files(path = "./simulated_data/d20year/theta_10",
                           # Identify all csv files in folder
                           pattern = "*.csv", full.names = TRUE) %>% 
  # Use fread from data.table to read in the files and store them in a list
  lapply(fread) %>%  
  # Use parLapply from parallel to apply stanbinner to each dataset in parallel
  parLapply(cl = cl, fun = stanbinner) 
twenty_year10b <- do.call(rbind, twenty_year10b)        # Combine data sets into one data set 
# check the data
head(twenty_year10b)  
# write.csv
write.csv(twenty_year10b, "./model_results/twenty_year_10b_metrics.csv")

#______________________________________________________________________

# Results for 20 year - 100
twenty_year100b <- list.files(path = "./simulated_data/d20year/theta_100",
                            # Identify all csv files in folder
                            pattern = "*.csv", full.names = TRUE) %>% 
  # Use fread from data.table to read in the files and store them in a list
  lapply(fread) %>%  
  # Use parLapply from parallel to apply stanbinner to each dataset in parallel
  parLapply(cl = cl, fun = stanbinner) 

twenty_year100b <- do.call(rbind, twenty_year100b)        # Combine data sets into one data set 
# check the data
head(twenty_year100b)  
# write.csv
write.csv(twenty_year100b, "./model_results/twenty_year_100b_metrics.csv")