diff --git a/PAPER_Conditional_probability_quantile_original_MEDMI_4_variables.Rout b/PAPER_Conditional_probability_quantile_original_MEDMI_4_variables.Rout
deleted file mode 100644
index 96ca0acf85a83c5d8d293c60c78c6d0a3bfd03e0..0000000000000000000000000000000000000000
--- a/PAPER_Conditional_probability_quantile_original_MEDMI_4_variables.Rout
+++ /dev/null
@@ -1,713 +0,0 @@
-
-R version 3.5.3 (2019-03-11) -- "Great Truth"
-Copyright (C) 2019 The R Foundation for Statistical Computing
-Platform: x86_64-pc-linux-gnu (64-bit)
-
-R is free software and comes with ABSOLUTELY NO WARRANTY.
-You are welcome to redistribute it under certain conditions.
-Type 'license()' or 'licence()' for distribution details.
-
- Natural language support but running in an English locale
-
-R is a collaborative project with many contributors.
-Type 'contributors()' for more information and
-'citation()' on how to cite R or R packages in publications.
-
-Type 'demo()' for some demos, 'help()' for on-line help, or
-'help.start()' for an HTML browser interface to help.
-Type 'q()' to quit R.
-
-[Previously saved workspace restored]
-
-> # The code does look at how the risk of Campylobacter in humans depends on environmental variables
-> #The code uses old MEDMI data (not corrected for altitude) and analysis done on regular division of the range of the environemtal varaibles rather than quantile.
->
->
-> rm(list=ls(all=TRUE))
-> #
-> library(ISOweek)
-> library(lubridate)
-
-Attaching package: ‘lubridate’
-
-The following object is masked from ‘package:base’:
-
- date
-
-> library(ggplot2)
-> require(MASS)
-Loading required package: MASS
-> library(scales)
-> require(pheno)
-Loading required package: pheno
-Loading required package: nlme
-Loading required package: SparseM
-
-Attaching package: ‘SparseM’
-
-The following object is masked from ‘package:base’:
-
- backsolve
-
-Loading required package: quantreg
-> library(timeDate)
-> library(pastecs)
-> library(stringi)
-> library(timeSeries)
-> #library(Hmisc)
->
-> #list.of.packages <- c("xts")
-> #new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
-> #if(length(new.packages)) install.packages(new.packages)
-> library(xts)
-Loading required package: zoo
-
-Attaching package: ‘zoo’
-
-The following object is masked from ‘package:timeSeries’:
-
- time<-
-
-The following objects are masked from ‘package:base’:
-
- as.Date, as.Date.numeric
-
-
-Attaching package: ‘xts’
-
-The following objects are masked from ‘package:pastecs’:
-
- first, last
-
->
->
->
->
-> ## Varaible file
->
-> variable_int<-"humidity"
-> variable_df_1<-read.csv(paste("../../Data_Base/OPIE_data_base/",variable_int,".csv",sep=""))
-> humidity<-variable_df_1[,-c(1,2)]
-> #dates<-as.Date(as.character(variable_df_1[-c(1,2),2]),format="%d/%m/%Y")
->
-> dates_s<-as.Date(as.character(variable_df_1[-c(1,2),2]),format="%Y-%m-%d")
-> dates<-rep(dates_s,times=length(variable_df_1)-2)
-> All_PC_s<-names(variable_df_1[1,])
-> All_PC_s<-All_PC_s[-c(1,2)]
-> All_PC<-rep(All_PC_s,each=length(dates_s))
->
->
-> width<-30
-> width_char<-paste(width)
->
->
->
-> variable_x<-"daylength"
-> #variable<-"daylength"
-> variable_y<-"Maximum_air_temperature"
-> variable<-"Relative_humidity"
-> #variable_x<-"Mean_wind_speed"
->
-> #variable_y<-"Mean_Precipitation"
-> #variable<-"daylength"
-> #variable<-"Mean_Precipitation"
-> #"Maximum_air_temperature",
-> #"Minimum_air_temperature",
-> #"Mean_wind_speed",
-> #"Mean_Precipitation",
-> #"Relative_humidity",
-> #"daylength"
->
->
-> Env_Campylobacter_data_all2<-read.csv(paste("../../Data_Base/Cases_Environment/Simulated_Campylobacter_environment_",width_char,"_original_MEDMI.csv",sep=""))
->
-> Env_Campylobacter_data_all2<-Env_Campylobacter_data_all2[,-1]
-> colnames(Env_Campylobacter_data_all2)<-c("PostCode","Date","Cases",
-+ "Maximum_air_temperature",
-+ "Minimum_air_temperature",
-+ "Mean_wind_speed",
-+ "Cumul_Precipitation",
-+ "Mean_Precipitation",
-+ "Relative_humidity",
-+ "daylength",
-+ "residents")
->
-> Env_laboratory_weekly<-read.csv(paste("../../Data_Base/Cases_Environment/Simulated_Laboratory_",width_char,"_original_MEDMI.csv",sep=""))
-> Env_laboratory_weekly<-Env_laboratory_weekly[,-1]
-> colnames(Env_laboratory_weekly)<-c("PostCode","Date",
-+ "Maximum_air_temperature",
-+ "Minimum_air_temperature",
-+ "Mean_wind_speed",
-+ "Cumul_Precipitation",
-+ "Mean_Precipitation",
-+ "Relative_humidity",
-+ "daylength",
-+ "residents")
->
->
->
->
-> Env_Campylobacter_data_int1<-subset(Env_Campylobacter_data_all2,year(as.Date(Env_Campylobacter_data_all2$Date))>=1990 & year(as.Date(Env_Campylobacter_data_all2$Date))<=2015)
-> Env_laboratory_int1<-subset(Env_laboratory_weekly,year(as.Date(Env_laboratory_weekly$Date))>=1990 & year(as.Date(Env_laboratory_weekly$Date))<=2015)
->
-> quarter<-1
-> quarter_char<-paste("_",as.character(quarter),"-quarter",sep="")
->
-> breaks_daylength<-(as.numeric(quantile(na.omit(Env_Campylobacter_data_int1$daylength), probs=seq(0,1, by=0.25), na.rm=TRUE)))
-> breaks_daylength[length(breaks_daylength)]<-ceiling((as.numeric(quantile(na.omit(Env_Campylobacter_data_int1$daylength), probs=seq(0,1, by=0.25), na.rm=TRUE))))[length(breaks_daylength)]
->
-> breaks_daylength[1]<-floor((as.numeric(quantile(na.omit(Env_Campylobacter_data_int1$daylength), probs=seq(0,1, by=0.25), na.rm=TRUE))))[1]
->
->
->
->
->
->
-> if (quarter==1){
-+ Env_Campylobacter_data_int1<-subset(Env_Campylobacter_data_all2,Env_Campylobacter_data_all2$daylength<=breaks_daylength[2])
-+ Env_laboratory_int1<-subset(Env_laboratory_weekly,Env_laboratory_weekly$daylength<=breaks_daylength[2])
-+ hours_char<-as.character(round(breaks_daylength[2]))
-+ }
->
-> if (quarter==2){
-+ Env_Campylobacter_data_int1<-subset(Env_Campylobacter_data_all2,Env_Campylobacter_data_all2$daylength>breaks_daylength[2] & Env_Campylobacter_data_all2$daylength<=breaks_daylength[3])
-+ Env_laboratory_int1<-subset(Env_laboratory_weekly,Env_laboratory_weekly$daylength>breaks_daylength[2] & Env_laboratory_weekly$daylength<=breaks_daylength[3])
-+ hours_char<-as.character(round(breaks_daylength[3]))
-+ }
->
-> if (quarter==3){
-+ Env_Campylobacter_data_int1<-subset(Env_Campylobacter_data_all2,Env_Campylobacter_data_all2$daylength>breaks_daylength[3] & Env_Campylobacter_data_all2$daylength<=breaks_daylength[4])
-+ Env_laboratory_int1<-subset(Env_laboratory_weekly,Env_laboratory_weekly$daylength>breaks_daylength[3] & Env_laboratory_weekly$daylength<=breaks_daylength[4])
-+ hours_char<-as.character(round(breaks_daylength[4]))
-+ }
->
-> if (quarter==4){
-+ Env_Campylobacter_data_int1<-subset(Env_Campylobacter_data_all2,Env_Campylobacter_data_all2$daylength>breaks_daylength[4])
-+ Env_laboratory_int1<-subset(Env_laboratory_weekly,Env_laboratory_weekly$daylength>breaks_daylength[4])
-+ hours_char<-as.character(round(breaks_daylength[5]))
-+ }
->
->
->
->
-> ################### include latitude and longitude
-> Coord_laboratory<-read.csv(paste("../../Data_Base/Cases/Lab_PostCodes.csv",sep=""))
->
->
-> lat_long_lab<-data.frame(names(Coord_laboratory),as.numeric(Coord_laboratory[1,]),as.numeric(Coord_laboratory[2,]))#
-> colnames(lat_long_lab)<-c("PostCode","lat","long")
->
-> Env_laboratory_int2<-merge(Env_laboratory_int1,lat_long_lab,by="PostCode")
-> Env_laboratory_int3<-data.frame(Env_laboratory_int2)
->
-> Env_Campylobacter_data_int2<-merge(Env_Campylobacter_data_int1,lat_long_lab,by="PostCode")
-> Env_Campylobacter_data_int3<-data.frame(Env_Campylobacter_data_int2)
->
->
->
-> ######################## include daylength ##################
->
-> PC_df<-data.frame(All_PC,as.Date(dates))
-> colnames(PC_df)<-c("PostCode","Date")
->
->
-> Post_Codes_df<-merge(PC_df,lat_long_lab,by="PostCode")
->
->
-> daylength<-function(lat,day_year)
-+ {
-+ #Latitude measure in degrees
-+ P <- asin(.39795*cos(.2163108 + 2*atan(.9671396*tan(.00860*(day_year-186)))))
-+ Denom<-cos(lat*pi/180)*cos(P)
-+ Numer<-sin(0.8333*pi/180) + sin(lat*pi/180)*sin(P)
-+ D<-24-(24/pi)*acos(Numer/Denom)
-+ return(D)
-+ }
->
-> latitude<-Post_Codes_df$lat
-> day_of_the_year<-yday(as.Date(Post_Codes_df$Date))
->
-> daylength_int1<-mapply(daylength, latitude, day_of_the_year)
-> daylength_df<-data.frame(latitude, day_of_the_year,as.Date(Post_Codes_df$Date),daylength_int1)
-> colnames(daylength_df)<-c("lat","day_year","Date","daylength")
-> daylength_df$Date<-as.factor(daylength_df$Date)
-> daylength_df$lat<-as.factor(daylength_df$lat)
-> Env_laboratory_int3$Date<-as.factor(Env_laboratory_int3$Date)
-> Env_laboratory_int3$lat<-as.factor(Env_laboratory_int3$lat)
->
-> #Env_laboratory_int4<-merge(Env_laboratory_int3,daylength_df,by=c("lat","Date"))
-> #Env_laboratory<-data.frame(Env_laboratory_int4)
-> Env_laboratory<-data.frame(Env_laboratory_int3)
-> Env_Campylobacter_data_int3$Date<-as.factor(Env_Campylobacter_data_int3$Date)
-> Env_Campylobacter_data_int3$lat <-as.factor(Env_Campylobacter_data_int3$lat)
->
->
-> #Env_Campylobacter_data_int4<-merge(Env_Campylobacter_data_int3,daylength_df,by=c("lat","Date"))
-> #Env_Campylobacter_data<-data.frame(Env_Campylobacter_data_int4)
-> Env_Campylobacter_data<-data.frame(Env_Campylobacter_data_int3)
->
->
->
->
->
-> ################### Divide the domains of the variables in bins according to quantiles
->
->
-> index_C<-which (names(Env_Campylobacter_data)==variable)
-> index_y_C<-which (names(Env_Campylobacter_data)==variable_y)
-> index_x_C<-which (names(Env_Campylobacter_data)==variable_x)
->
-> index_res_C<-which (names(Env_Campylobacter_data)=="residents")
->
->
-> index<-which (names(Env_laboratory)==variable)
-> index_y<-which (names(Env_laboratory)==variable_y)
-> index_x<-which (names(Env_laboratory)==variable_x)
-> index_res<-which (names(Env_laboratory)=="residents")
->
->
-> #########################
->
->
-> breaks_z_lab<-function(variable,by_z)
-+ {
-+
-+ index<-which (names(Env_laboratory)==variable)
-+
-+
-+ breaks_z<-as.numeric(quantile(na.omit(Env_laboratory[,index]), probs=seq(0,1, by=by_z), na.rm=TRUE))
-+ breaks_z[length(breaks_z)]<-ceiling(as.numeric(quantile(na.omit(Env_laboratory[,index]), probs=seq(0,1, by=by_z), na.rm=TRUE)))[length(breaks_z)]
-+ breaks_z[1]<-floor(as.numeric(quantile(na.omit(Env_laboratory[,index]), probs=seq(0,1, by=by_z), na.rm=TRUE)))[1]
-+
-+
-+ return(breaks_z)
-+
-+ }
->
->
->
-> breaks_z<-function(variable,by_z)
-+ {
-+
-+ index_C<-which (names(Env_Campylobacter_data)==variable)
-+
-+ breaks_z<-as.numeric(quantile(na.omit(Env_Campylobacter_data[,index_C]), probs=seq(0,1, by=by_z), na.rm=TRUE))
-+
-+ breaks_z[length(breaks_z)]<-ceiling(as.numeric(quantile(na.omit(Env_Campylobacter_data[,index_C]), probs=seq(0,1, by=by_z), na.rm=TRUE)))[length(breaks_z)]
-+ breaks_z[1]<-floor(as.numeric(quantile(na.omit(Env_Campylobacter_data[,index_C]), probs=seq(0,1, by=by_z), na.rm=TRUE)))[1]
-+
-+
-+ return(breaks_z)
-+
-+ }
->
->
->
->
-> breaks_y_lab<-function(variable,variable_y,by_z,by_y,j_z)
-+ {
-+
-+ index_C<-which (names(Env_Campylobacter_data)==variable)
-+
-+ index<-which (names(Env_laboratory)==variable)
-+ index_y<-which (names(Env_laboratory)==variable_y)
-+
-+
-+
-+ wt<-(findInterval(Env_Campylobacter_data[,index_C],breaks_z(variable,by_z)))
-+ ww<-which(wt==j_z)
-+ Env_Campylobacter_data_some<-Env_Campylobacter_data[ww,]
-+
-+ wt<-(findInterval(Env_laboratory[,index],breaks_z(variable,by_z)))
-+ ww<-which(wt==j_z)
-+ Env_laboratory_some<-Env_laboratory[ww,]
-+
-+ if (length(Env_Campylobacter_data_some[,1])!=0) {
-+
-+ breaks_y<-as.numeric(quantile(na.omit(Env_laboratory_some[,index_y]), probs=seq(0,1, by=by_y), na.rm=TRUE))
-+ breaks_y[length(breaks_y)]<-ceiling(as.numeric(quantile(na.omit(Env_laboratory_some[,index_y]), probs=seq(0,1, by=by_y), na.rm=TRUE)))[length(breaks_y)]
-+ breaks_y[1]<-floor(as.numeric(quantile(na.omit(Env_laboratory_some[,index_y]), probs=seq(0,1, by=by_y), na.rm=TRUE)))[1]
-+
-+ }else{
-+
-+ breaks_y<-c()
-+ }
-+
-+ return(breaks_y)
-+ }
->
->
->
-> breaks_y<-function(variable,variable_y,by_z,by_y,j_z)
-+ {
-+
-+ index_C<-which (names(Env_Campylobacter_data)==variable)
-+ index_y_C<-which (names(Env_Campylobacter_data)==variable_y)
-+
-+
-+
-+ wt<-(findInterval(Env_Campylobacter_data[,index_C],breaks_z(variable,by_z)))
-+ ww<-which(wt==j_z)
-+ Env_Campylobacter_data_some<-Env_Campylobacter_data[ww,]
-+
-+
-+ if (length(Env_Campylobacter_data_some[,1])!=0) {
-+
-+ breaks_y<-as.numeric(quantile(na.omit(Env_Campylobacter_data_some[,index_y_C]), probs=seq(0,1, by=by_y), na.rm=TRUE))
-+ breaks_y[length(breaks_y)]<-ceiling(as.numeric(quantile(na.omit(Env_Campylobacter_data_some[,index_y_C]), probs=seq(0,1, by=by_y), na.rm=TRUE)))[length(breaks_y)]
-+ breaks_y[1]<-floor(as.numeric(quantile(na.omit(Env_Campylobacter_data_some[,index_y_C]), probs=seq(0,1, by=by_y), na.rm=TRUE)))[1]
-+
-+ }else{
-+
-+ breaks_y<-c()
-+ }
-+
-+ return(breaks_y)
-+ }
->
->
->
-> breaks_x_lab<-function(variable,variable_y,variable_x,by_z,by_y,by_x,j_z,j_y)
-+ {
-+ index_C<-which (names(Env_Campylobacter_data)==variable)
-+ index_y_C<-which (names(Env_Campylobacter_data)==variable_y)
-+
-+
-+ index<-which (names(Env_laboratory)==variable)
-+ index_y<-which (names(Env_laboratory)==variable_y)
-+ index_x<-which (names(Env_laboratory)==variable_x)
-+
-+ if(is.na(breaks_y(variable,variable_y,by_z,by_y,j_z)[j_y])=='FALSE'){
-+
-+ wt<-(findInterval(Env_Campylobacter_data[,index_y_C],breaks_y(variable,variable_y,by_z,by_y,j_z)))
-+ ww<-which(wt==j_y)
-+ Env_Campylobacter_data_some<-Env_Campylobacter_data[ww,]
-+
-+ if (length(Env_Campylobacter_data_some[,1])!=0) {
-+
-+ wt<-(findInterval(Env_laboratory[,index_y],breaks_y(variable,variable_y,by_z,by_y,j_z)))
-+ ww<-which(wt==j_y)
-+ Env_laboratory_some<-Env_laboratory[ww,]
-+
-+
-+ breaks_x<-as.numeric(quantile(na.omit(Env_laboratory_some[,index_x]), probs=seq(0,1, by=by_x), na.rm=TRUE))
-+ breaks_x[length(breaks_x)]<-ceiling(as.numeric(quantile(na.omit(Env_laboratory_some[,index_x]), probs=seq(0,1, by=by_x), na.rm=TRUE)))[length(breaks_x)]
-+ breaks_x[1]<-floor(as.numeric(quantile(na.omit(Env_laboratory_some[,index_x]), probs=seq(0,1, by=by_x), na.rm=TRUE)))[1]
-+
-+ } else {
-+
-+ breaks_x<-c()
-+ } } else {
-+
-+ breaks_x<-c()
-+
-+ }
-+
-+ return(breaks_x)
-+ }
->
->
-> breaks_x<-function(variable,variable_y,variable_x,by_z,by_y,by_x,j_z,j_y)
-+ {
-+ index_C<-which (names(Env_Campylobacter_data)==variable)
-+ index_y_C<-which (names(Env_Campylobacter_data)==variable_y)
-+ index_x_C<-which (names(Env_Campylobacter_data)==variable_x)
-+
-+ if(is.na(breaks_y(variable,variable_y,by_z,by_y,j_z)[j_y])=='FALSE'){
-+
-+ wt<-(findInterval(Env_Campylobacter_data[,index_y_C],breaks_y(variable,variable_y,by_z,by_y,j_z)))
-+ ww<-which(wt==j_y)
-+ Env_Campylobacter_data_some<-Env_Campylobacter_data[ww,]
-+
-+ if (length(Env_Campylobacter_data_some[,1])!=0) {
-+
-+ wt<-(findInterval(Env_Campylobacter_data_some[,index_y_C],breaks_y(variable,variable_y,by_z,by_y,j_z)))
-+ ww<-which(wt==j_y)
-+ Env_Campylobacter_data_some2<-Env_Campylobacter_data_some[ww,]
-+
-+
-+ breaks_x<-as.numeric(quantile(na.omit(Env_Campylobacter_data_some2[,index_x_C]), probs=seq(0,1, by=by_x), na.rm=TRUE))
-+ breaks_x[length(breaks_x)]<-ceiling(as.numeric(quantile(na.omit(Env_Campylobacter_data_some2[,index_x_C]), probs=seq(0,1, by=by_x), na.rm=TRUE)))[length(breaks_x)]
-+ breaks_x[1]<-floor(as.numeric(quantile(na.omit(Env_Campylobacter_data_some2[,index_x_C]), probs=seq(0,1, by=by_x), na.rm=TRUE)))[1]
-+
-+ } else
-+ { breaks_x<-c()
-+ }
-+ }
-+ else {
-+
-+ breaks_x<-c()
-+
-+ }
-+
-+ return(breaks_x)
-+ }
->
->
-> #################
->
->
->
->
-> var_x_loc_df<-data.frame(character(), character(),character(),numeric(),numeric(),numeric())
-> colnames(var_x_loc_df)<-c(variable,variable_y,variable_x,"counts","residents","residents_tot")
->
-> residents_i_var<-0
-> residents_universal<-0
-> #i_var_max<-length(breaks_var)
-> #i_var_min<-1
-> #i_var_max_x<-length(breaks_var_x)
-> #i_var_min_x<-1
->
->
-> #####################
-> by_z<-0.25
-> by_y<-0.25
-> by_x<-0.1
->
-> #i_var_min<-breaks_z(variable,by_z)[1]
-> #i_var_max<-breaks_z(variable,by_z)[length(breaks_z(variable,by_z))]
-> j_z_min<-1
-> j_z_max<-length(breaks_z(variable,by_z))-1
->
->
->
-> for (j_z in c(j_z_min:j_z_max))
-+ {
-+
-+ wt<-(findInterval((Env_Campylobacter_data[,index_C]),breaks_z(variable,by_z)))
-+ ww<-which(wt==j_z)
-+ Env_Campylobacter_data_z<-Env_Campylobacter_data[ww,]
-+
-+ wt<-(findInterval((Env_laboratory[,index]),breaks_z(variable,by_z)))
-+ ww<-which(wt==j_z)
-+ Env_laboratory_z<-Env_laboratory[ww,]
-+
-+ if (length(Env_Campylobacter_data_z[,1])!=0){
-+ if (length(breaks_y(variable,variable_y,by_z,by_y,j_z))!=0){
-+
-+ j_y_min<-1
-+ j_y_max<-length(breaks_y(variable,variable_y,by_z,by_y,j_z))-1
-+
-+
-+
-+ for (j_y in c(j_y_min:j_y_max))
-+ {
-+
-+ wt<-(findInterval((Env_Campylobacter_data_z[,index_y_C]),breaks_y(variable,variable_y,by_z,by_y,j_z)))
-+ ww<-which(wt==j_y)
-+ Env_Campylobacter_data_y<-Env_Campylobacter_data_z[ww,]
-+
-+ wt<-(findInterval((Env_laboratory_z[,index_y]),breaks_y(variable,variable_y,by_z,by_y,j_z)))
-+ ww<-which(wt==j_y)
-+ Env_laboratory_y<-Env_laboratory_z[ww,]
-+
-+
-+ if (length(breaks_x(variable,variable_y,variable_x,by_z,by_y,by_x,j_z,j_y))!=0){
-+
-+ j_x_min<-1
-+ j_x_max<- length(breaks_x(variable,variable_y,variable_x,by_z,by_y,by_x,j_z,j_y))-1
-+ for (j_x in c(j_x_min:j_x_max))
-+ {
-+
-+
-+ wt<-(findInterval((Env_Campylobacter_data_y[,index_x_C]),breaks_x(variable,variable_y,variable_x,by_z,by_y,by_x,j_z,j_y)))
-+ ww<-which(wt==j_x)
-+ Yt1<-Env_Campylobacter_data_y[ww,c(1:3,index_C,index_y_C,index_x_C,index_res_C)]
-+
-+ wt<-(findInterval((Env_laboratory[,index_x]),breaks_x(variable,variable_y,variable_x,by_z,by_y,by_x,j_z,j_y)))
-+ ww<-which(wt==j_x)
-+ Y_tot<-Env_laboratory_y[ww,c(1:2,index,index_y,index_x,index_res)]
-+
-+ Total_cases<-sum((as.numeric(na.omit(Yt1$Cases))))
-+ residents<-sum((as.numeric(na.omit(Yt1$residents))))
-+ residents_tot<-sum((as.numeric(na.omit(Y_tot$residents))))
-+
-+ data_df<-data.frame(
-+ breaks_z(variable,by_z)[j_z],
-+ breaks_y(variable,variable_y,by_z,by_y,j_z)[j_y],
-+ breaks_x(variable,variable_y,variable_x,by_z,by_y,by_x,j_z,j_y)[j_x],
-+ Total_cases,
-+ residents,
-+ residents_tot)
-+
-+
-+
-+
-+
-+ colnames(data_df)<-c(variable,variable_y,variable_x,"counts","residents","residents_tot")
-+ var_x_loc_df<-rbind(var_x_loc_df,data_df)
-+ print(c(j_x,j_y,j_z, Total_cases))
-+
-+ }}}
-+ }
-+
-+
-+ }}
-[1] 1 1 1 1064
-[1] 2 1 1 577
-[1] 3 1 1 666
-[1] 4 1 1 1040
-[1] 5 1 1 1142
-[1] 6 1 1 1908
-[1] 7 1 1 3095
-[1] 8 1 1 3122
-[1] 9 1 1 5401
-[1] 10 1 1 7128
-[1] 1 2 1 972
-[1] 2 2 1 1162
-[1] 3 2 1 1138
-[1] 4 2 1 1236
-[1] 5 2 1 1345
-[1] 6 2 1 1647
-[1] 7 2 1 2838
-[1] 8 2 1 4556
-[1] 9 2 1 5122
-[1] 10 2 1 6251
-[1] 1 3 1 546
-[1] 2 3 1 1029
-[1] 3 3 1 1317
-[1] 4 3 1 1434
-[1] 5 3 1 1368
-[1] 6 3 1 1511
-[1] 7 3 1 2429
-[1] 8 3 1 4258
-[1] 9 3 1 6212
-[1] 10 3 1 6036
-[1] 1 4 1 583
-[1] 2 4 1 924
-[1] 3 4 1 1381
-[1] 4 4 1 1748
-[1] 5 4 1 2166
-[1] 6 4 1 2818
-[1] 7 4 1 3349
-[1] 8 4 1 4162
-[1] 9 4 1 4605
-[1] 10 4 1 4829
-[1] 1 1 2 2805
-[1] 2 1 2 2811
-[1] 3 1 2 2238
-[1] 4 1 2 2192
-[1] 5 1 2 2184
-[1] 6 1 2 2473
-[1] 7 1 2 1871
-[1] 8 1 2 2275
-[1] 9 1 2 2927
-[1] 10 1 2 2494
-[1] 1 2 2 2278
-[1] 2 2 2 1901
-[1] 3 2 2 1997
-[1] 4 2 2 1828
-[1] 5 2 2 1534
-[1] 6 2 2 3887
-[1] 7 2 2 4279
-[1] 8 2 2 3363
-[1] 9 2 2 3020
-[1] 10 2 2 1476
-[1] 1 3 2 1982
-[1] 2 3 2 2525
-[1] 3 3 2 2501
-[1] 4 3 2 2431
-[1] 5 3 2 2381
-[1] 6 3 2 3492
-[1] 7 3 2 4241
-[1] 8 3 2 3423
-[1] 9 3 2 2183
-[1] 10 3 2 464
-[1] 1 4 2 2163
-[1] 2 4 2 2214
-[1] 3 4 2 3260
-[1] 4 4 2 3809
-[1] 5 4 2 3482
-[1] 6 4 2 3064
-[1] 7 4 2 2886
-[1] 8 4 2 2295
-[1] 9 4 2 1985
-[1] 10 4 2 1811
-[1] 1 1 3 2036
-[1] 2 1 3 2310
-[1] 3 1 3 2636
-[1] 4 1 3 2704
-[1] 5 1 3 2889
-[1] 6 1 3 2771
-[1] 7 1 3 2501
-[1] 8 1 3 2471
-[1] 9 1 3 2219
-[1] 10 1 3 2837
-[1] 1 2 3 3304
-[1] 2 2 3 3872
-[1] 3 2 3 3600
-[1] 4 2 3 3187
-[1] 5 2 3 3171
-[1] 6 2 3 3000
-[1] 7 2 3 1250
-[1] 8 2 3 1670
-[1] 9 2 3 1061
-[1] 10 2 3 1435
-[1] 1 3 3 4450
-[1] 2 3 3 3521
-[1] 3 3 3 3370
-[1] 4 3 3 2844
-[1] 5 3 3 2559
-[1] 6 3 3 2693
-[1] 7 3 3 2134
-[1] 8 3 3 1003
-[1] 9 3 3 1157
-[1] 10 3 3 1715
-[1] 1 4 3 3517
-[1] 2 4 3 2242
-[1] 3 4 3 2944
-[1] 4 4 3 2524
-[1] 5 4 3 2988
-[1] 6 4 3 2336
-[1] 7 4 3 2505
-[1] 8 4 3 2344
-[1] 9 4 3 2953
-[1] 10 4 3 2954
-[1] 1 1 4 2784
-[1] 2 1 4 2783
-[1] 3 1 4 2913
-[1] 4 1 4 2629
-[1] 5 1 4 2895
-[1] 6 1 4 2777
-[1] 7 1 4 3256
-[1] 8 1 4 3555
-[1] 9 1 4 2018
-[1] 10 1 4 943
-[1] 1 2 4 2603
-[1] 2 2 4 3785
-[1] 3 2 4 3606
-[1] 4 2 4 3612
-[1] 5 2 4 3323
-[1] 6 2 4 2484
-[1] 7 2 4 2889
-[1] 8 2 4 2143
-[1] 9 2 4 1459
-[1] 10 2 4 365
-[1] 1 3 4 2931
-[1] 2 3 4 4489
-[1] 3 3 4 4386
-[1] 4 3 4 5211
-[1] 5 3 4 4429
-[1] 6 3 4 2361
-[1] 7 3 4 514
-[1] 8 3 4 1240
-[1] 9 3 4 985
-[1] 10 3 4 228
-[1] 1 4 4 4817
-[1] 2 4 4 6199
-[1] 3 4 4 5312
-[1] 4 4 4 3519
-[1] 5 4 4 2500
-[1] 6 4 4 1596
-[1] 7 4 4 1211
-[1] 8 4 4 1051
-[1] 9 4 4 980
-[1] 10 4 4 466
->
->
-> write.csv(var_x_loc_df,paste("../../Data_Base/Cases_Environment/Conditional_probability_",variable,"_",variable_y,"_",variable_x,"_",width_char,"_",hours_char,"_Simulated_for_rec_original_MEDMI_quantile.csv",sep=""))
->
-> proc.time()
- user system elapsed
-319.283 9.656 328.960