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ANALYSE_hilfscode.R
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ANALYSE_hilfscode.R
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setwd("/home/dao/Desktop/MasterArbeit/R_files/KNITR/")
load(file = "FULL_FINAL_WORKSPACE.Rdata")
#### packages ####
library("ggplot2")
library("rgdal")
library("sp")
library("plyr")
library("ggplot2")
library("scales")
library("ENmisc")
library("gridExtra")
library("Hmisc")
library("dplyr")
library("car")
library("vcd")
library("plyr")
bpDF <- subset(LOR4reg@data, !is.na(Gentri))
bpDF$Gentri <- factor(bpDF$Gentri,levels(bpDF$Gentri)[c(2,3,1)])
bpDF$GentriA <- factor(bpDF$GentriA,levels(bpDF$GentriA)[c(2,3,1)])
levels(bpDF$valid)[levels(bpDF$valid)=="gültig"] <- "Gesamt"
bpGentriInnere <- subset(bpDF, Gentri=="Gentri" & STADTRAUM=="innere Stadt")
bpGesamtInnere <- subset(bpDF, STADTRAUM=="innere Stadt")
# Gentri: GENTRI Quantilsgrenzen
qntl_Armutchg <- wtd.quantile(LOR4reg@data$Armutchg, weights=LOR4reg@data$E_E.2007,
probs=c(0, .25, .5, .75, 1))
qntl_Mietechgr <- wtd.quantile(LOR4reg@data$Mietechgr, weights=LOR4reg@data$E_E.2007,
probs=c(0, .25, .5, .75, 1))
# GentriA: GENTRI Quantilsgrenzen
qntlA_Armutchg <- wtd.quantile(LOR4reg@data$Armutchg, weights=LOR4reg@data$E_E.2007,
probs=c(0, .15, .5, .85, 1))
qntlA_Mietechgr <- wtd.quantile(LOR4reg@data$Mietechgr, weights=LOR4reg@data$E_E.2007,
probs=c(0, .15, .5, .85, 1))
bp_theme <- theme(axis.title.x = element_blank(),
plot.margin=unit(c(0.5,-0.3,0.5,0.5), "cm"),
legend.position="none")
bp_themeMITRAND <- theme(axis.title.x = element_blank(),
legend.position="none")
bp_themeG <- theme(axis.text.y = element_blank(),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.ticks = element_blank(),
plot.margin=unit(c(0.5,0.5,0.5,-0.3), "cm"),
legend.position="none")
brueche <- 8
##### Mietechgr ####
p1Mietechgr <- ggplot(bpDF, aes(Gentri,
Mietechgr,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste(Delta[r],'Miete (%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche))+
geom_violin(scale = "width") + bp_theme
p1Mietechgr <- p1Mietechgr + geom_boxplot(width=.3)
p1Mietechgr <- p1Mietechgr + geom_hline(aes(yintercept=qntl_Mietechgr[4]),
linetype="dotted", color="red", size=1)
p2Mietechgr <- ggplot(bpDF, aes(valid,
Mietechgr,
weight=E_E.2007)) +
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
geom_violin(scale="width") + bp_themeG
p2Mietechgr <- p2Mietechgr + geom_boxplot(width=.3)
p2Mietechgr <- p2Mietechgr + geom_hline(aes(yintercept=qntl_Mietechgr[4]),
linetype="dotted", color="red", size=1)
p2Mietechgr <- p2Mietechgr + annotate("text", x=0.6, y=4.55, label="Q[0.75]", parse=TRUE, col="red")
#p2Mietechgr
grid.arrange(p1Mietechgr,p2Mietechgr, ncol=2, nrow=1, widths=c(3,1))
##### Armutchg ####
p1Armutchg <- ggplot(bpDF, aes(Gentri,
Armutchg,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste(Delta,'Armut (%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche))+
geom_violin(scale = "width") + bp_theme
p1Armutchg <- p1Armutchg + geom_boxplot(width=.3)
p1Armutchg <- p1Armutchg + geom_hline(aes(yintercept=qntl_Armutchg[2]),
linetype="dotted", color="red", size=1)
p2Armutchg <- ggplot(bpDF, aes(valid,
Armutchg,
weight=E_E.2007)) +
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
geom_violin(scale="width") + bp_themeG
p2Armutchg <- p2Armutchg + geom_boxplot(width=.3)
p2Armutchg <- p2Armutchg + geom_hline(aes(yintercept=qntl_Armutchg[2]),
linetype="dotted", color="red", size=1)
p2Armutchg <- p2Armutchg + annotate("text", x=1.4, y=-3.6, label="Q[0.25]", parse=TRUE, col="red")
#p2Armutchg
#grid.arrange(p1Armutchg, p2Armutchg, ncol=2, nrow=1, widths=c(3,1))
##### Miete 2007 ####
p1Miete.2007 <- ggplot(bpDF, aes(Gentri,
Miete.2007,
weight=E_E.2007,
fill=Gentri)) +
#ylab("Miete 2007")+
ylab(expression(paste(Miete[2007],' ','(€)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche))+
geom_violin(scale = "width") + bp_theme
p1Miete.2007 <- p1Miete.2007 + geom_boxplot(width=.3)
p1Miete.2007 <- p1Miete.2007 + geom_segment(mapping=aes(x="Gentri", y=Gentri_Miete.2007_0.10,
xend="Kontroll", yend=Gentri_Miete.2007_0.10),
linetype="dotted", color="red", size=0.5) +
geom_segment(mapping=aes(x="Gentri", y=Gentri_Miete.2007_0.90,
xend="Kontroll", yend=Gentri_Miete.2007_0.90),
linetype="dotted", color="red", size=0.5)
p1Miete.2007 <- p1Miete.2007 +
annotate("text", x=1.5, y=7.4, label="Q[0.9]^Gentri", parse=TRUE, col="red") +
annotate("text", x=1.5, y=4.9, label="Q[0.1]^Gentri", parse=TRUE, col="red")
#p1Miete.2007
p2Miete.2007 <- ggplot(bpDF, aes(valid,
Miete.2007,
weight=E_E.2007)) +
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
geom_violin(scale="width") + bp_themeG
p2Miete.2007 <- p2Miete.2007 + geom_boxplot(width=.3)
#grid.arrange(p1Miete.2007, p2Miete.2007, ncol=2, nrow=1, widths=c(3,1))
##### Armut 2007 ####
p1Armut.2007 <- ggplot(bpDF, aes(Gentri,
Armut.2007,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste(Armut[2007],' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=5))+
geom_violin(scale = "width") + bp_theme
p1Armut.2007 <- p1Armut.2007 + geom_boxplot(width=.3)
p1Armut.2007 <- p1Armut.2007 + geom_segment(mapping=aes(x="Gentri", y=Gentri_Armut.2007_0.10,
xend="Kontroll", yend=Gentri_Armut.2007_0.10),
linetype="dotted", color="red", size=0.5) +
geom_segment(mapping=aes(x="Gentri", y=Gentri_Armut.2007_0.90,
xend="Kontroll", yend=Gentri_Armut.2007_0.90),
linetype="dotted", color="red", size=0.5)
p1Armut.2007 <- p1Armut.2007 +
annotate("text", x=1.5, y=46.5, label="Q[0.9]^Gentri", parse=TRUE, col="red") +
annotate("text", x=1.5, y=15.5, label="Q[0.1]^Gentri", parse=TRUE, col="red")
# p1Armut.2007
p2Armut.2007 <- ggplot(bpDF, aes(valid,
Armut.2007,
weight=E_E.2007)) +
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
geom_violin(scale="width") + bp_themeG
p2Armut.2007 <- p2Armut.2007 + geom_boxplot(width=.3)
#grid.arrange(p1Armut.2007, p2Armut.2007, ncol=2, nrow=1, widths=c(3,1))
##### Miete 2012 ####
p1Miete.2012 <- ggplot(bpDF, aes(Gentri,
Miete.2012,
weight=E_E.2007,
fill=Gentri)) +
#ylab("Miete 2007")+
ylab(expression(paste(Miete[2012],' ','(€)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche))+
geom_violin(scale = "width") + bp_theme
p1Miete.2012<- p1Miete.2012 + geom_boxplot(width=.3)
#p1Miete.2012
p2Miete.2012 <- ggplot(bpDF, aes(valid,
Miete.2012,
weight=E_E.2007)) +
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
geom_violin(scale="width") + bp_themeG
p2Miete.2012 <- p2Miete.2012 + geom_boxplot(width=.3)
grid.arrange(p1Miete.2012, p2Miete.2012, ncol=2, nrow=1, widths=c(3,1))
##### Armut 2012 ####
p1Armut.2012 <- ggplot(bpDF, aes(Gentri,
Armut.2012,
weight=E_E.2007,
fill=Gentri)) +
#ylab("Miete 2007")+
ylab(expression(paste(Armut[2012],' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche))+
geom_violin(scale = "width") + bp_theme
p1Armut.2012 <- p1Armut.2012 + geom_boxplot(width=.3)
p2Armut.2012 <- ggplot(bpDF, aes(valid,
Armut.2012,
weight=E_E.2007)) +
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
geom_violin(scale="width") + bp_themeG
p2Armut.2012 <- p2Armut.2012 + geom_boxplot(width=.3)
grid.arrange(p1Armut.2012, p2Armut.2012, ncol=2, nrow=1, widths=c(3,1))
grid.arrange(p1Mietechgr, p2Mietechgr, p1Armutchg, p2Armutchg,
p1Miete.2007, p2Miete.2007, p1Armut.2007, p2Armut.2007,
ncol=4, nrow=2, widths=c(3,1,3,1,3,1,3,1))
grid.arrange(p1Mietechgr, p2Mietechgr, p1Armutchg, p2Armutchg,
p1Miete.2007, p2Miete.2007, p1Armut.2007, p2Armut.2007,
p1Miete.2012, p2Miete.2012, p1Armut.2012, p2Armut.2012,
ncol=4, nrow=3, widths=c(3,1,3,1,3,1,3,1,3,1,3,1))
View(bpDF)
##### H1 Boxplots ####
#**** innere stadt ****##
p1ArmutG.2007 <- ggplot(bpGentriInnere , aes(Gentri,
Armut.2007,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste(Armut[2007],' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche),
limits=c(4, 52))+
geom_violin(scale = "width") + bp_theme
p1ArmutG.2007 <- p1ArmutG.2007 + geom_boxplot(width=.3)
p1ArmutG.2007
p2ArmutG.2007 <- ggplot(bpGesamtInnere, aes(valid,
Armut.2007,
weight=E_E.2007)) +
scale_y_continuous(breaks=pretty_breaks(n=brueche),
limits=c(4, 52)) +
geom_violin(scale="width") + bp_themeG
p2ArmutG.2007 <- p2ArmutG.2007 + geom_boxplot(width=.3)
p2ArmutG.2007
grid.arrange(p1ArmutG.2007, p2ArmutG.2007,
ncol=2, nrow=1, widths=c(1,1))
p1MieteG.2007 <- ggplot(bpGentriInnere , aes(Gentri,
Miete.2007,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste(Miete[2007],' ','(Euro)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche),
limits=c(4.7, 10.9))+
geom_violin(scale = "width") + bp_theme
p1MieteG.2007 <- p1MieteG.2007 + geom_boxplot(width=.3)
p1MieteG.2007
p2MieteG.2007 <- ggplot(bpGesamtInnere, aes(valid,
Miete.2007,
weight=E_E.2007)) +
scale_y_continuous(breaks=pretty_breaks(n=brueche),
limits=c(4.7, 10.9)) +
geom_violin(scale="width") + bp_themeG
p2MieteG.2007 <- p2MieteG.2007 + geom_boxplot(width=.3)
p2MieteG.2007
grid.arrange(p1MieteG.2007, p2MieteG.2007,
ncol=2, nrow=1, widths=c(1,1))
grid.arrange(p1MieteG.2007, p2MieteG.2007,
p1ArmutG.2007, p2ArmutG.2007,
ncol=4, nrow=1, widths=c(1,1,1,1))
barMiete.2007I <- ggplot(data=bpGesamtInnere, aes(x=Miete.2007, fill=Gentri)) +
geom_bar(width=0.5, binwidth=1, colour="white",size=1) +
theme(axis.title.y = element_text(face="bold",colour = "grey50"),
axis.title.x = element_text(face="bold",colour = "grey50"),
legend.text=element_text(colour = "grey50"),
legend.title=element_text(face="bold",colour = "grey50"),
legend.title=element_text(size=rel(0.7), face="bold"),
legend.text=element_text(size=rel(0.5))) +
scale_x_continuous(breaks=seq(4,11,1), limits=c(4,11)) +
scale_y_continuous(breaks=seq(0,60,10)) +
xlab(expression(paste(Miete[2007],' ','(Euro/',m^{2},')'))) +
ylab(expression(paste('Anzahl der LOR'))) +
guides(fill=guide_legend(title="Kategorie"))
barMiete.2007I
grid.arrange(p1MieteG.2007, p2MieteG.2007, barMiete.2007I,
ncol=3, nrow=1, widths=c(1,1,2))
barArmut.2007I <- ggplot(data=bpGesamtInnere, aes(x=Armut.2007, fill=Gentri)) +
geom_bar(width=0.5, binwidth=5, colour="white",size=1) +
theme(axis.title.y = element_text(face="bold",colour = "grey50"),
axis.title.x = element_text(face="bold",colour = "grey50"),
legend.text=element_text(colour = "grey50"),
legend.title=element_text(face="bold",colour = "grey50"),
legend.title=element_text(size=rel(0.7), face="bold"),
legend.text=element_text(size=rel(0.5))) +
scale_x_continuous(breaks=seq(0,60,10), limits=c(0,60)) +
scale_y_continuous(breaks=seq(0,35,10)) +
xlab(expression(paste(Armut[2007],' ','(%)'))) +
ylab(expression(paste('Anzahl der LOR'))) +
guides(fill=guide_legend(title="Kategorie"))
barArmut.2007I
grid.arrange(p1ArmutG.2007, p2ArmutG.2007, barArmut.2007I,
ncol=3, nrow=1, widths=c(1,1,2))
#oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo
#---- +++ Robustheitscheck von H 1 mit alternativer Klassifizierung +++ -----
#oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo
#***** innere Stadt ******#
bpGentriAInnere <- subset(bpDF, GentriA=="Gentri" & STADTRAUM=="innere Stadt")
p1ArmutG.2007 <- ggplot(bpGentriAInnere , aes(GentriA,
Armut.2007,
weight=E_E.2007,
fill=GentriA)) +
ylab(expression(paste(Armut[2007],' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche),
limits=c(4, 52))+
geom_violin(scale = "width") + bp_theme
p1ArmutG.2007 <- p1ArmutG.2007 + geom_boxplot(width=.3)
p1ArmutG.2007
p2ArmutG.2007 <- ggplot(bpGesamtInnere, aes(valid,
Armut.2007,
weight=E_E.2007)) +
scale_y_continuous(breaks=pretty_breaks(n=brueche),
limits=c(4, 52)) +
geom_violin(scale="width") + bp_themeG
p2ArmutG.2007 <- p2ArmutG.2007 + geom_boxplot(width=.3)
p2ArmutG.2007
grid.arrange(p1ArmutG.2007, p2ArmutG.2007,
ncol=2, nrow=1, widths=c(1,1))
p1MieteG.2007 <- ggplot(bpGentriAInnere , aes(GentriA,
Miete.2007,
weight=E_E.2007,
fill=GentriA)) +
ylab(expression(paste(Miete[2007],' ','(Euro)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche),
limits=c(4.7, 10.9))+
geom_violin(scale = "width") + bp_theme
p1MieteG.2007 <- p1MieteG.2007 + geom_boxplot(width=.3)
p1MieteG.2007
p2MieteG.2007 <- ggplot(bpGesamtInnere, aes(valid,
Miete.2007,
weight=E_E.2007)) +
scale_y_continuous(breaks=pretty_breaks(n=brueche),
limits=c(4.7, 10.9)) +
geom_violin(scale="width") + bp_themeG
p2MieteG.2007 <- p2MieteG.2007 + geom_boxplot(width=.3)
p2MieteG.2007
grid.arrange(p1MieteG.2007, p2MieteG.2007,
ncol=2, nrow=1, widths=c(1,1))
grid.arrange(p1MieteG.2007, p2MieteG.2007,
p1ArmutG.2007, p2ArmutG.2007,
ncol=4, nrow=1, widths=c(1,1,1,1))
barMiete.2007I <- ggplot(data=bpGesamtInnere, aes(x=Miete.2007, fill=GentriA)) +
geom_bar(width=0.5, binwidth=1, colour="white",size=1) +
theme(axis.title.y = element_text(face="bold",colour = "grey50"),
axis.title.x = element_text(face="bold",colour = "grey50"),
legend.text=element_text(colour = "grey50"),
legend.title=element_text(face="bold",colour = "grey50"),
legend.title=element_text(size=rel(0.7), face="bold"),
legend.text=element_text(size=rel(0.5))) +
scale_x_continuous(breaks=seq(4,11,1), limits=c(4,11)) +
scale_y_continuous(breaks=seq(0,60,10)) +
xlab(expression(paste(Miete[2007],' ','(Euro/',m^{2},')'))) +
ylab(expression(paste('Anzahl der LOR'))) +
guides(fill=guide_legend(title="Kategorie"))
barMiete.2007I
grid.arrange(p1MieteG.2007, p2MieteG.2007, barMiete.2007I,
ncol=3, nrow=1, widths=c(1,1,2))
barArmut.2007I <- ggplot(data=bpGesamtInnere, aes(x=Armut.2007, fill=GentriA)) +
geom_bar(width=0.5, binwidth=5, colour="white",size=1) +
theme(axis.title.y = element_text(face="bold",colour = "grey50"),
axis.title.x = element_text(face="bold",colour = "grey50"),
legend.text=element_text(colour = "grey50"),
legend.title=element_text(face="bold",colour = "grey50"),
legend.title=element_text(size=rel(0.7), face="bold"),
legend.text=element_text(size=rel(0.5))) +
scale_x_continuous(breaks=seq(0,60,10), limits=c(0,60)) +
scale_y_continuous(breaks=seq(0,35,10)) +
xlab(expression(paste(Armut[2007],' ','(%)'))) +
ylab(expression(paste('Anzahl der LOR'))) +
guides(fill=guide_legend(title="Kategorie"))
barArmut.2007I
grid.arrange(p1ArmutG.2007, p2ArmutG.2007, barArmut.2007I,
ncol=3, nrow=1, widths=c(1,1,2))
##### H2 Boxplots ####
#####**** gesamte Stadt ****####
p1FortzuegeR <- ggplot(bpDF , aes(Gentri,
FortzuegeR,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste('Fortzüge',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(3, 17)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1FortzuegeR <- p1FortzuegeR + geom_boxplot(width=.3)
p1FortzuegeR
p1FortzuegeUDAR <- ggplot(bpDF , aes(Gentri,
FortzuegeUDAR,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste('FortzügeA',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(0, 10)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1FortzuegeUDAR <- p1FortzuegeUDAR + geom_boxplot(width=.3)
p1FortzuegeUDAR
p1ZuzuegeR <- ggplot(bpDF , aes(Gentri,
ZuzuegeR,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste('Zuzüge',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1ZuzuegeR <- p1ZuzuegeR + geom_boxplot(width=.3)
p1ZuzuegeR
p1ZuzuegeUDAR <- ggplot(bpDF , aes(Gentri,
ZuzuegeUDAR,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste('ZuzügeA',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(0, 15)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1ZuzuegeUDAR <- p1ZuzuegeUDAR+ geom_boxplot(width=.3)
p1ZuzuegeUDAR
grid.arrange(p1FortzuegeR, p1ZuzuegeR,
p1FortzuegeUDAR, p1ZuzuegeUDAR,
ncol=2, nrow=2, widths=c(1,1,1,1))
#####**** innere Stadt ****####
p1FortzuegeRI <- ggplot(bpGesamtInnere, aes(Gentri,
FortzuegeR,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste('Fortzüge',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(3, 17)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1FortzuegeRI <- p1FortzuegeRI + geom_boxplot(width=.3)
#p1FortzuegeRI
p1FortzuegeUDARI <- ggplot(bpGesamtInnere, aes(Gentri,
FortzuegeUDAR,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste('FortzügeA',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(1,10)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1FortzuegeUDARI <- p1FortzuegeUDARI + geom_boxplot(width=.3)
#p1FortzuegeUDARI
p1ZuzuegeRI <- ggplot(bpGesamtInnere, aes(Gentri,
ZuzuegeR,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste('Zuzüge',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(5, 22)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1ZuzuegeRI <- p1ZuzuegeRI + geom_boxplot(width=.3)
#p1ZuzuegeRI
p1ZuzuegeUDARI <- ggplot(bpGesamtInnere, aes(Gentri,
ZuzuegeUDAR,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste('ZuzügeA',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(1, 14)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1ZuzuegeUDARI <- p1ZuzuegeUDARI + geom_boxplot(width=.3)
#p1ZuzuegeUDARI
grid.arrange(p1FortzuegeRI, p1ZuzuegeRI,
p1FortzuegeUDARI, p1ZuzuegeUDARI,
ncol=2, nrow=2, widths=c(1,1,1,1))
#oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo
#---- +++ Robustheitscheck von H 2 mit alternativer Klassifizierung +++ -----
#oooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooo
#***** gesamte Stadt ******#
p1FortzuegeR <- ggplot(bpDF , aes(GentriA,
FortzuegeR,
weight=E_E.2007,
fill=GentriA)) +
ylab(expression(paste('Fortzüge',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(3, 17)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1FortzuegeR <- p1FortzuegeR + geom_boxplot(width=.3)
p1FortzuegeUDAR <- ggplot(bpDF , aes(GentriA,
FortzuegeUDAR,
weight=E_E.2007,
fill=GentriA)) +
ylab(expression(paste('FortzügeA',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(0, 10)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1FortzuegeUDAR <- p1FortzuegeUDAR + geom_boxplot(width=.3)
p1ZuzuegeR <- ggplot(bpDF , aes(GentriA,
ZuzuegeR,
weight=E_E.2007,
fill=GentriA)) +
ylab(expression(paste('Zuzüge',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1ZuzuegeR <- p1ZuzuegeR + geom_boxplot(width=.3)
p1ZuzuegeUDAR <- ggplot(bpDF , aes(GentriA,
ZuzuegeUDAR,
weight=E_E.2007,
fill=GentriA)) +
ylab(expression(paste('ZuzügeA',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(0, 15)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1ZuzuegeUDAR <- p1ZuzuegeUDAR+ geom_boxplot(width=.3)
grid.arrange(p1FortzuegeR, p1ZuzuegeR,
p1FortzuegeUDAR, p1ZuzuegeUDAR,
ncol=2, nrow=2, widths=c(1,1,1,1))
#***** innere Stadt ******#
p1FortzuegeRI <- ggplot(bpGesamtInnere, aes(GentriA,
FortzuegeR,
weight=E_E.2007,
fill=GentriA)) +
ylab(expression(paste('Fortzüge',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(3, 17)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1FortzuegeRI <- p1FortzuegeRI + geom_boxplot(width=.3)
#p1FortzuegeRI
p1FortzuegeUDARI <- ggplot(bpGesamtInnere, aes(GentriA,
FortzuegeUDAR,
weight=E_E.2007,
fill=GentriA)) +
ylab(expression(paste('FortzügeA',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(1,10)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1FortzuegeUDARI <- p1FortzuegeUDARI + geom_boxplot(width=.3)
#p1FortzuegeUDARI
p1ZuzuegeRI <- ggplot(bpGesamtInnere, aes(GentriA,
ZuzuegeR,
weight=E_E.2007,
fill=GentriA)) +
ylab(expression(paste('Zuzüge',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(5, 22)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1ZuzuegeRI <- p1ZuzuegeRI + geom_boxplot(width=.3)
#p1ZuzuegeRI
p1ZuzuegeUDARI <- ggplot(bpGesamtInnere, aes(GentriA,
ZuzuegeUDAR,
weight=E_E.2007,
fill=GentriA)) +
ylab(expression(paste('ZuzügeA',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(1, 14)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1ZuzuegeUDARI <- p1ZuzuegeUDARI + geom_boxplot(width=.3)
#p1ZuzuegeUDARI
grid.arrange(p1FortzuegeRI, p1ZuzuegeRI,
p1FortzuegeUDARI, p1ZuzuegeUDARI,
ncol=2, nrow=2, widths=c(1,1,1,1))
#********************************************
# #
# LONG DATA #
# #
#********************************************
bpDFlong <- subset(LORdataFULLvalid, ZEIT==2007 | ZEIT==2012)
bpDFlong$ZEIT <- factor(bpDFlong$ZEIT)
bpDFlong$Gentri <- factor(bpDFlong$Gentri,levels(bpDFlong$Gentri)[c(2,3,1)])
bpDFlong$GentriA <- factor(bpDFlong$GentriA,levels(bpDFlong$GentriA)[c(2,3,1)])
bpDFlong$valid <- as.factor("Gesamt")
bpDFlong$ZEITvalid <- interaction(bpDFlong$ZEIT,bpDFlong$valid)
levels(bpDFlong$ZEITvalid) <- c("Gesamt 2007","Gesamt 2012")
bpDFlong$ZEITGentri <- interaction(bpDFlong$ZEIT,bpDFlong$Gentri)
levels(bpDFlong$ZEITGentri) <- c("Gentri 2007","Gentri 2012",
"Kontroll 2007", "Kontroll 2012",
"Andere 2007", "Andere 2012")
##### Miete 2007-2012 ####
p1Miete.2007_2012 <- ggplot(bpDFlong, aes(x=ZEITGentri,
y=Miete,
fill=Gentri,
weight=E_E)) +
ylab("Miete (€)")+
scale_y_continuous(breaks=pretty_breaks(n=brueche))+
geom_violin(scale = "width") + bp_theme
p1Miete.2007_2012 <- p1Miete.2007_2012 + geom_boxplot(width=.3)
p1Miete.2007_2012
p2Miete.2007_2012 <- ggplot(bpDFlong, aes(x=ZEITvalid,
y=Miete,
weight=E_E)) +
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
geom_violin(scale="width") + bp_themeG
p2Miete.2007_2012 <- p2Miete.2007_2012 + geom_boxplot(width=.3)
grid.arrange(p1Miete.2007_2012, p2Miete.2007_2012, ncol=2, nrow=1, widths=c(3,1))
##### Armut 2007-2012 ####
p1Armut.2007_2012 <- ggplot(bpDFlong, aes(x=ZEITGentri,
y=Armut,
fill=Gentri,
weight=E_E)) +
ylab("Armut (%)")+
scale_y_continuous(breaks=pretty_breaks(n=brueche))+
geom_violin(scale = "width") + bp_theme
p1Armut.2007_2012 <- p1Armut.2007_2012 + geom_boxplot(width=.3)
p1Armut.2007_2012
p2Armut.2007_2012 <- ggplot(bpDFlong, aes(x=ZEITvalid,
y=Armut,
weight=E_E)) +
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
geom_violin(scale="width") + bp_themeG
p2Armut.2007_2012 <- p2Armut.2007_2012 + geom_boxplot(width=.3)
grid.arrange(p1Armut.2007_2012, p2Armut.2007_2012, ncol=2, nrow=1, widths=c(3,1))
##### MOSAIC PLOT: MietechgrQNTLS*ArmutchgQNTLS ######
fill_colors <- matrix(c("red", "gray", "gray","grey",
"gray", "gray", "gray","grey",
"gray", "gray", "gray","grey",
"gray", "gray", "gray","grey"), ncol = 4)
bpDF$MietechgrQNTL <- factor(bpDF$MietechgrQNTL,levels(bpDF$MietechgrQNTL)[c(4,3,2,1)])
mosaicDF <- table(bpDF$MietechgrQNTL, bpDF$ArmutchgQNTL,dnn=c("Relative Mietpressteigerung","Änderung der Armutsquote"))
levels(bpDF$valid)[levels(bpDF$valid)=="gültig"] <- "Gesamt"
levels(bpDF$MietechgrQNTL)[levels(bpDF$MietechgrQNTL)=="4.Quartil"] <- "4.Qrt"
levels(bpDF$MietechgrQNTL)[levels(bpDF$MietechgrQNTL)=="3.Quartil"] <- "3.Qrt"
levels(bpDF$MietechgrQNTL)[levels(bpDF$MietechgrQNTL)=="2.Quartil"] <- "2.Qrt"
levels(bpDF$MietechgrQNTL)[levels(bpDF$MietechgrQNTL)=="1.Quartil"] <- "1.Qrt"
levels(bpDF$ArmutchgQNTL)[levels(bpDF$ArmutchgQNTL)=="4.Quartil"] <- "4.Qrt"
levels(bpDF$ArmutchgQNTL)[levels(bpDF$ArmutchgQNTL)=="3.Quartil"] <- "3.Qrt"
levels(bpDF$ArmutchgQNTL)[levels(bpDF$ArmutchgQNTL)=="2.Quartil"] <- "2.Qrt"
levels(bpDF$ArmutchgQNTL)[levels(bpDF$ArmutchgQNTL)=="1.Quartil"] <- "1.Qrt"
mosaic(mosaicDF, gp = gpar(fill = fill_colors, col = 0))
assoc(mosaicDF,shade=TRUE)
summary(bpDF$Gentri)
table(bpDF$STADTRAUM,bpDF$Gentri)
summary(bpDF$STADTRAUM)
ddply(bpDF, .(Gentri), summarize,
#dist2STADTMITTE_mean=round(weighted.mean(dist2STADTMITTE), digits=0),
dist2STADTMITTE_median=round(median(dist2STADTMITTE), digits=0),
E_E.2007_median=round(median(E_E.2007), digits=0),
E_E.2007_sum=sum(E_E.2007),
Mietechgr_mean=round(weighted.mean(Mietechgr,E_E.2007),digits=1),
Miete.2007_mean=round(weighted.mean(Miete.2007,E_E.2007),digits=2),
Miete.2012_mean=round(weighted.mean(Miete.2012,E_E.2007),digits=2),
Armutchg_mean=round(weighted.mean(Armutchg,E_E.2007),digits=1) ,
Armut.2007_mean=round(weighted.mean(Armut.2007,E_E.2007),digits=1),
Armut.2012_mean=round(weighted.mean(Armut.2012,E_E.2007),digits=1)) -> summaryGENTRI
write.table(summaryGENTRI,file="/home/dao/Desktop/MasterArbeit/R_files/KNITR/TabellenSkizzen/summaryGENTRI.csv",
quote=T,append=F,sep=";",eol = "\n", na = "NA", dec = ",", row.names = T,col.names = T)
summaryGENTRI$dist2STADTMITTE_median
summaryGENTRI$E_E.2007_median
summaryGENTRI$E_E.2007_sum
Mietechgr_qntl <- wtd.quantile(bpDF$Mietechgr, weights=bpDF$E_E.2007,
probs=c(0, .25, .5, .75, 1))
Mietechgr_qntl[4]
Armutchg_qntl <- wtd.quantile(bpDF$Armutchg, weights=bpDF$E_E.2007,
probs=c(0, .25, .5, .75, 1))
Armutchg_qntl[2]
Gentri_Miete.2007_0.10
Gentri_Miete.2007_0.90
Gentri_Armut.2007_0.10
Gentri_Armut.2007_0.90
summarize(bpDF,
dist2STADTMITTE_median=round(median(dist2STADTMITTE), digits=0),
E_E.2007_median=round(median(E_E.2007), digits=0),
E_E.2007_sum=sum(E_E.2007),
Mietechgr_mean=round(weighted.mean(Mietechgr,E_E.2007),digits=1),
Miete.2007_mean=round(weighted.mean(Miete.2007,E_E.2007),digits=2),
Miete.2012_mean=round(weighted.mean(Miete.2012,E_E.2007),digits=2),
Armutchg_mean=round(weighted.mean(Armutchg,E_E.2007),digits=1) ,
Armut.2007_mean=round(weighted.mean(Armut.2007,E_E.2007),digits=1),
Armut.2012_mean=round(weighted.mean(Armut.2012,E_E.2007),digits=1))
bar_theme <- theme(#axis.text.y = element_text(colour = "grey20",size =16),
axis.title.y = element_blank(),
axis.title.x = element_text(face="bold",colour = "grey50"),
#legend.text=element_text(colour = "grey20",size=14),
legend.title=element_text(face="bold",colour = "grey50"))
summaryBEZ_NAME <- ddply(bpDF,
.(BEZ_NAME, Gentri), summarize,
E_E.2007_sum=sum(E_E.2007))
summaryBEZ_NAME <- arrange(summaryBEZ_NAME, Gentri, E_E.2007_sum)
names(summaryBEZ_NAME)[names(summaryBEZ_NAME)=="Gentri"] <- "Kategorie"
summaryBEZ_NAME$E_E.2007_sum <- summaryBEZ_NAME$E_E.2007_sum/1000
Reihenfolge <- rev(c("Friedrichshain-Kreuzberg","Neukölln",
"Pankow","Lichtenberg",
"Charlottenburg-Wilmersdorf",
"Treptow-Köpenick", "Mitte",
"Tempelhof-Schöneberg","Spandau","Reinickendorf",
"Marzahn-Hellersdorf","Steglitz-Zehlendorf"))
bar1 <- ggplot(data=summaryBEZ_NAME, aes(x=factor(BEZ_NAME, levels=Reihenfolge), y=E_E.2007_sum, fill=Kategorie)) +
geom_bar(stat='identity') + bar_theme + ylab("Einwohner*innenzahl 2007 in 1000") + coord_flip()
bar1
##### Unterschiede GENTRI / KONTROLL ####
p1 <- ggplot(bpDF, aes(Gentri,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste('Fortzüge',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(3, 17)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1FortzuegeRI <- p1FortzuegeRI + geom_boxplot(width=.3)
#p1FortzuegeRI
p1FortzuegeUDARI <- ggplot(bpGesamtInnere, aes(Gentri,
FortzuegeUDAR,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste('FortzügeA',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(1,10)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1FortzuegeUDARI <- p1FortzuegeUDARI + geom_boxplot(width=.3)
#p1FortzuegeUDARI
p1ZuzuegeRI <- ggplot(bpGesamtInnere, aes(Gentri,
ZuzuegeR,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste('Zuzüge',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(5, 22)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1ZuzuegeRI <- p1ZuzuegeRI + geom_boxplot(width=.3)
#p1ZuzuegeRI
p1ZuzuegeUDARI <- ggplot(bpGesamtInnere, aes(Gentri,
ZuzuegeUDAR,
weight=E_E.2007,
fill=Gentri)) +
ylab(expression(paste('ZuzügeA',' ','(%)')))+
scale_y_continuous(breaks=pretty_breaks(n=brueche)) +
coord_cartesian(ylim = c(1, 14)) +
geom_violin(scale = "width") + bp_themeMITRAND
p1ZuzuegeUDARI <- p1ZuzuegeUDARI + geom_boxplot(width=.3)
#p1ZuzuegeUDARI
grid.arrange(p1FortzuegeRI, p1ZuzuegeRI,
p1FortzuegeUDARI, p1ZuzuegeUDARI,
ncol=2, nrow=2, widths=c(1,1,1,1))
boxplot(bpDF$E_65U110R.2007 ~ bpDF$Gentri)
boxplot(bpDF$E_65U110R.2012 ~ bpDF$Gentri)
boxplot(bpDF$E_18U35R.2007 ~ bpDF$Gentri)
boxplot(bpDF$E_18U35R.2012 ~ bpDF$Gentri)
boxplot(bpDF$E_18U35Rchg ~ bpDF$Gentri)
boxplot(bpDF$E_65U110Rchg ~ bpDF$Gentri)
boxplot(bpDF$AlleinerzHH.2012 ~ bpDF$Gentri)
boxplot(bpDF$HK_Turkchg ~ bpDF$Gentri)
boxplot(bpDF$HK_TurkRchg ~ bpDF$Gentri)
boxplot(bpDF$HK_ArabRchg ~ bpDF$Gentri)
boxplot(bpDF$MH_ERchg ~ bpDF$Gentri)
boxplot(bpDF$HK_EU15Rchg ~ bpDF$Gentri)
boxplot(bpDF$HK_EU27Rchg ~ bpDF$Gentri)
boxplot(bpDF$HK_EheJugRMHchg ~ bpDF$Gentri)
boxplot(bpDF$HK_EU27RMHhg ~ bpDF$Gentri)
boxplot(bpDF$MH_65U110R65U110chg ~ bpDF$Gentri)
boxplot(bpDF$MH_ERchg ~ bpDF$Gentri)
table(bpDF$SanGebiet.2012, bpDF$Gentri)
######### Statistiken zu Aufwertung ######
MietechgrMEANI <- round(weighted.mean(bpDF$Mietechgr[bpDF$STADTRAUM=="innere Stadt"],
bpDF$E_E.2007[bpDF$STADTRAUM=="innere Stadt"]),2)
MietechgrMEANI
MietechgrMEANA <- round(weighted.mean(bpDF$Mietechgr[bpDF$STADTRAUM!="innere Stadt"],
bpDF$E_E.2007[bpDF$STADTRAUM!="innere Stadt"]),2)
MietechgrMEANA
ArmutchgMEANI <- round(weighted.mean(bpDF$Armutchg[bpDF$STADTRAUM=="innere Stadt"],
bpDF$E_E.2007[bpDF$STADTRAUM=="innere Stadt"]),2)
ArmutchgMEANI
ArmutchgMEANA <- round(weighted.mean(bpDF$Armutchg[bpDF$STADTRAUM!="innere Stadt"],
bpDF$E_E.2007[bpDF$STADTRAUM!="innere Stadt"]),2)
ArmutchgMEANA
#### __MOBILITÄTSRATEN Statistiken__ ####
#### FortzügeR Vergleich ####
wtd.mean(x=bpDF$FortzuegeR[bpDF$GentriA=="Gentri"],
weights=bpDF$E_E.2007[bpDF$GentriA=="Gentri"])
wtd.mean(x=bpDF$FortzuegeR[bpDF$GentriA=="Kontroll"],
weights=bpDF$E_E.2007[bpDF$GentriA=="Kontroll"])
wtd.mean(x=bpDF$FortzuegeR,
weights=bpDF$E_E.2007)
wtd.mean(x=bpDF$FortzuegeUDAR,
weights=bpDF$E_E.2007)
wtd.mean(x=bpDF$ZuzuegeR,
weights=bpDF$E_E.2007)
wtd.mean(x=bpDF$ZuzuegeUDAR,
weights=bpDF$E_E.2007)
wtd.quantile(x=bpDF$FortzuegeR,
weights=bpDF$E_E.2007,
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpDF$FortzuegeUDAR,
weights=bpDF$E_E.2007,
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpDF$ZuzuegeR,
weights=bpDF$E_E.2007,
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpDF$ZuzuegeUDAR,
weights=bpDF$E_E.2007,
probs=c(0, .25, .5, .75, 1))
wtd.mean(x=bpGesamtInnere$FortzuegeR[bpGesamtInnere$Gentri=="Gentri"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Gentri"])
wtd.mean(x=bpGesamtInnere$FortzuegeR[bpGesamtInnere$Gentri=="Kontroll"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Kontroll"])
#----- TAB dist2Stadtmitte -----
wtd.quantile(x=bpDF$dist2STADTMITTE,
weights=bpDF$E_E.2007,
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpDF$dist2STADTMITTE[bpDF$Gentri=="Gentri"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Gentri"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpDF$dist2STADTMITTE[bpDF$Gentri=="Kontroll"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Kontroll"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpDF$dist2STADTMITTE[bpDF$Gentri=="Andere"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Andere"],
probs=c(0, .25, .5, .75, 1))
#---- TAB FortzuegeR -----
wtd.quantile(x=bpDF$FortzuegeR[bpDF$Gentri=="Gentri"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Gentri"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpDF$FortzuegeR[bpDF$Gentri=="Kontroll"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Kontroll"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpGesamtInnere$FortzuegeR[bpGesamtInnere$Gentri=="Gentri"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Gentri"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpGesamtInnere$FortzuegeR[bpGesamtInnere$Gentri=="Kontroll"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Kontroll"],
probs=c(0, .25, .5, .75, 1))
#### ZuzügeR Vergleich ####
wtd.mean(x=bpDF$ZuzuegeR[bpDF$Gentri=="Gentri"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Gentri"])
wtd.mean(x=bpDF$ZuzuegeR[bpDF$Gentri=="Kontroll"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Kontroll"])
wtd.mean(x=bpGesamtInnere$ZuzuegeR[bpGesamtInnere$Gentri=="Gentri"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Gentri"])
wtd.mean(x=bpGesamtInnere$ZuzuegeR[bpGesamtInnere$Gentri=="Kontroll"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Kontroll"])
wtd.quantile(x=bpDF$ZuzuegeR[bpDF$Gentri=="Gentri"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Gentri"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpDF$ZuzuegeR[bpDF$Gentri=="Kontroll"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Kontroll"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpGesamtInnere$ZuzuegeR[bpGesamtInnere$Gentri=="Gentri"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Gentri"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpGesamtInnere$ZuzuegeR[bpGesamtInnere$Gentri=="Kontroll"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Kontroll"],
probs=c(0, .25, .5, .75, 1))
#### FortzuegeUDAR Vergleich ####
wtd.mean(x=bpDF$FortzuegeUDAR[bpDF$Gentri=="Gentri"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Gentri"])
wtd.mean(x=bpDF$FortzuegeUDAR[bpDF$Gentri=="Kontroll"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Kontroll"])
wtd.mean(x=bpGesamtInnere$FortzuegeUDAR[bpGesamtInnere$Gentri=="Gentri"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Gentri"])
wtd.mean(x=bpGesamtInnere$FortzuegeUDAR[bpGesamtInnere$Gentri=="Kontroll"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Kontroll"])
wtd.quantile(x=bpDF$FortzuegeUDAR[bpDF$Gentri=="Gentri"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Gentri"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpDF$FortzuegeUDAR[bpDF$Gentri=="Kontroll"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Kontroll"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpGesamtInnere$FortzuegeUDAR[bpGesamtInnere$Gentri=="Gentri"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Gentri"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpGesamtInnere$FortzuegeUDAR[bpGesamtInnere$Gentri=="Kontroll"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Kontroll"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpGesamtInnere$FortzuegeUDAR,
weights=bpGesamtInnere$E_E.2007,
probs=c(0, .25, .5, .75, 1))
#### ZuzügeUDAR Vergleich ####
wtd.mean(x=bpDF$ZuzuegeUDAR[bpDF$Gentri=="Gentri"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Gentri"])
wtd.mean(x=bpDF$ZuzuegeUDAR[bpDF$Gentri=="Kontroll"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Kontroll"])
wtd.mean(x=bpGesamtInnere$ZuzuegeUDAR[bpGesamtInnere$Gentri=="Gentri"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Gentri"])
wtd.mean(x=bpGesamtInnere$ZuzuegeUDAR[bpGesamtInnere$Gentri=="Kontroll"],
weights=bpGesamtInnere$E_E.2007[bpGesamtInnere$Gentri=="Kontroll"])
wtd.quantile(x=bpDF$ZuzuegeUDAR[bpDF$Gentri=="Gentri"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Gentri"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpDF$ZuzuegeUDAR[bpDF$Gentri=="Kontroll"],
weights=bpDF$E_E.2007[bpDF$Gentri=="Kontroll"],
probs=c(0, .25, .5, .75, 1))
wtd.quantile(x=bpGesamtInnere$ZuzuegeUDAR[bpGesamtInnere$Gentri=="Gentri"],