stl pca run

# Clear workspace to get rid of old junk
#rm(list=ls(all=TRUE))

#These 2 packages need to be installed and loaded first
#install.packages('devtools')
require(devtools)
#install.packages('abind')
require(abind)

#read in function file--can read directly from github using devtools function 'source_url'
source_url("https://raw.githubusercontent.com/weinbergerlab/Brazil_state/master/functions%20glm%20aic%20mod%20ave.R")      
#source('functions glm aic mod ave.R')

packages <- c('RCurl','reshape2','RColorBrewer','matlib','lme4', 'dummy','rstanarm','knitr','plotly','MASS', 'parallel','splines', 'lubridate','devtools')
packageHandler(packages, update_packages = FALSE, install_packages = FALSE) #change to true if need to install any
sapply(packages, library, quietly = TRUE, character.only = TRUE)


#Set working directory: default to desktop--different path for windows vs Mac
if(.Platform$OS.type == "windows") {
  desktop<-file.path(Sys.getenv("USERPROFILE"),"Desktop")
} else {
  desktop<- "~/Desktop"
}

setwd(desktop)

n_seasons=12 #12 for monthly, 4 for quarterly, 3 for triannually
N.sim=10000 #total number of random draws for the predictive distribution
bivariate=FALSE  #two control variables or 1 in regression?

###############USER SPECIFIED VALUES
#Note us data on github has sparse counts set to 99999
for(country.select in c('Brazil','Chile','Ecuador','Mexico')){
country=country.select

if(country=="Brazil"){
  all_cause_name <- 'ach_noj'
  strata_name<-"age_group"
  all_cause_pneu_name <- 'J12_18'
  date_name<-'date'
  data_start_date <- as.Date('2004-01-01')   #When do you want the analysis to start? (yyyy-mm-01)
  data_intervention_start<-as.Date('2010-01-01')   #When is the intervention introduced?  (yyyy-mm-01)
  N.buffer=24 #How many months before start evaluation?
  git.data= getURL("https://raw.githubusercontent.com/weinbergerlab/synthetic-control/master/Datasets%20for%20PNAS/Dataset%20S1%20Brazil.csv")      
}else if(country=="Chile"){
  all_cause_name <- 'ach_noj'
  strata_name<-"age_group"
  all_cause_pneu_name <- 'J12_18'
  date_name<-'date'
  data_start_date <- as.Date('2001-01-01')   #When do you want the analysis to start? (yyyy-mm-01)
  data_intervention_start<-as.Date('2011-01-01')   #When is the intervention introduced?  (yyyy-mm-01)
  N.buffer=12 #How many months before start evaluation?
  git.data= getURL("https://raw.githubusercontent.com/weinbergerlab/synthetic-control/master/Datasets%20for%20PNAS/Dataset%20S2%20Chile.csv")      
}else if(country=="Ecuador"){
  all_cause_name <- 'ach_noj'
  strata_name<-"age_group"
  all_cause_pneu_name <- 'J12_18'
  date_name<-'date'
  data_start_date <- as.Date('2001-01-01')   #When do you want the analysis to start? (yyyy-mm-01)
  data_intervention_start<-as.Date('2010-01-01')   #When is the intervention introduced?  (yyyy-mm-01)
  N.buffer=24 #How many months before start evaluation?
  git.data= getURL("https://raw.githubusercontent.com/weinbergerlab/synthetic-control/master/Datasets%20for%20PNAS/Dataset%20S3%20Ecuador.csv")      
}else if(country=="Mexico"){
  all_cause_name <- 'ach_noj'
  strata_name<-"age_group"
  all_cause_pneu_name <- 'J12_18'
  date_name<-'date'
  data_start_date <- as.Date('2000-01-01')   #When do you want the analysis to start? (yyyy-mm-01)
  data_intervention_start<-as.Date('2006-01-01')   #When is the intervention introduced?  (yyyy-mm-01)
  N.buffer=24 #How many months before start evaluation?
  git.data= getURL("https://raw.githubusercontent.com/weinbergerlab/synthetic-control/master/Datasets%20for%20PNAS/Dataset%20S4%20Mexico.csv")      
}else if(country=="US"){
  all_cause_name <- 'ach_sid_noresp'
  strata_name<-"age_group"
  all_cause_pneu_name <- 'm_ACP'
  date_name<-'date'
  data_start_date <- as.Date('1994-01-01')   #When do you want the analysis to start? (yyyy-mm-01)
  data_intervention_start<-as.Date('2000-01-01')   #When is the intervention introduced?  (yyyy-mm-01)
  N.buffer=24 #How many months before start evaluation?
  git.data= getURL("https://raw.githubusercontent.com/weinbergerlab/synthetic-control/master/Datasets%20for%20PNAS/Dataset%20S5%20US%20pneu.csv")      
}

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

#IMPORT DATA (default is to read Brazil state-level data from github..can change read.csv to a file saved on computer)
d1 <- read.csv(text=git.data)
print(country)
#Run the analysis
source_url("https://raw.githubusercontent.com/weinbergerlab/Brazil_state/master/stl_pca_parallel_analysis")

}