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run_analysis.R
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run_analysis.R
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rm(list = ls())
# disable scientific notation
options(scipen = 999)
# set warning level
options(warn = -1)
start_time <- Sys.time()
source("R/functions.R")
# define needed packages
packages <- c("reshape2", "ggplot2", "readr", "readxl", "countrycode", "dplyr", "openxlsx", "beepr", "zoo", "foreach", "doParallel")
# check if needed packags are installed and do so, if not
ipak(packages)
# load default settings
source("R/settings.R")
# prepare common data
source("R/prepare_data.R")
# base ----
settings <- settings_default
# modify experiment name
settings$exp_name <- "base"
# modify model complexity
settings$regressors <- c("gdp_pc", "I(gdp_pc^2)", "spatial", "recession",
"pop_dens", "urb_share", "temporal")
settings$plotting <- FALSE
# prepare run
settings <- prepare_run(settings)
source("R/analysis.R")
# convergence measure -----
settings <- settings_default
# modify experiment name
settings$exp_name <- "conv"
# modify model complexity
settings$regressors <- c("gdp_pc", "I(gdp_pc^2)", "spatial", "recession",
"pop_dens", "urb_share", "temporal", "ratio_gdp_pc2glob")
settings$plotting <- FALSE
# prepare run
settings <- prepare_run(settings)
source("R/analysis.R")
# population weights ----
settings <- settings_default
# modify experiment name
settings$exp_name <- "conv_pop"
# modify model complexity
settings$regressors <- c("gdp_pc", "I(gdp_pc^2)", "spatial", "recession",
"pop_dens", "urb_share", "temporal", "ratio_gdp_pc2glob")
# use weighed regression
settings$regression_weights <- "pop"
settings$plotting <- FALSE
# prepare run
settings <- prepare_run(settings)
source("R/analysis.R")
# population weights with nx ----
# load default settings
settings <- settings_default
# modify experiment name
settings$exp_name <- "conv_pop_nx"
# modify model complexity
settings$regressors <- c("gdp_pc", "I(gdp_pc^2)", "spatial", "recession",
"pop_dens", "urb_share", "nx_pc_share", "temporal", "ratio_gdp_pc2glob")
# # other modifications
settings$plotting <- FALSE
# use weighed regression
settings$regression_weights <- "pop"
# prepare run
settings <- prepare_run(settings)
source("R/analysis.R")
# gdp weights ----
# load default settings
settings <- settings_default
# modify experiment name
settings$exp_name <- "conv_gdp"
# modify model complexity
settings$regressors <- c("gdp_pc", "I(gdp_pc^2)", "spatial", "recession",
"pop_dens", "urb_share", "temporal", "ratio_gdp_pc2glob")
# # other modifications
settings$plotting <- FALSE
# use weighed regression
settings$regression_weights <- "gdp"
# prepare run
settings <- prepare_run(settings)
source("R/analysis.R")
# gdp weights with nx ----
# load default settings
settings <- settings_default
# modify experiment name
settings$exp_name <- "conv_gdp_nx"
# modify model complexity
settings$regressors <- c("gdp_pc", "I(gdp_pc^2)", "spatial", "recession",
"pop_dens", "urb_share", "nx_pc_share", "temporal", "ratio_gdp_pc2glob")
# # other modifications
settings$plotting <- FALSE
# use weighed regression
settings$regression_weights <- "gdp"
# prepare run
settings <- prepare_run(settings)
source("R/analysis.R")
# compare runs ---
source("R/compare_runs.R")
# play a sound to that you know the run is finished and elasped time
beep(sound = 2, print(Sys.time() - start_time))