# pre-processing of the data
# 1) keep only stayers and movers
# 2) regress wages on agedum + agedum * period2 , remove interaction only
#' plot the mean wage at origin conditional on where it is coming from
plot.wage <- function(jdata) {
rr = jdata[, {
fit = lm(y2 ~ bs(y1,df=10), .SD)
xnew = quantile(y1,seq(0.05,0.95,l=100))
list(y1=y1,y2=predict(fit))
},list(j1,j2)]
rr = jdata[,mean(y2),list(j1,j2)]
ggplot(rr,aes(x=j1,y=V1,color=j2 , group=j2)) + geom_line() + theme_bw()
rr = jdata[,mean(y2-y1),list(j1,j2)]
ggplot(rr,aes(x=j1,y=V1,color=j2 , group=j2)) + geom_line() + theme_bw()
# check education / gender / age per cluster
rr = jdata[,.N,]
}
# Multiple plot function
#
# ggplot objects can be passed in ..., or to plotlist (as a list of ggplot objects)
# - cols: Number of columns in layout
# - layout: A matrix specifying the layout. If present, 'cols' is ignored.
#
# If the layout is something like matrix(c(1,2,3,3), nrow=2, byrow=TRUE),
# then plot 1 will go in the upper left, 2 will go in the upper right, and
# 3 will go all the way across the bottom.
#
multiplot <- function(..., plotlist=NULL, file, cols=1, layout=NULL) {
require(grid)
# Make a list from the ... arguments and plotlist
plots <- c(list(...), plotlist)
numPlots = length(plots)
# If layout is NULL, then use 'cols' to determine layout
if (is.null(layout)) {
# Make the panel
# ncol: Number of columns of plots
# nrow: Number of rows needed, calculated from # of cols
layout <- matrix(seq(1, cols * ceiling(numPlots/cols)),
ncol = cols, nrow = ceiling(numPlots/cols))
}
if (numPlots==1) {
print(plots[[1]])
} else {
# Set up the page
grid.newpage()
pushViewport(viewport(layout = grid.layout(nrow(layout), ncol(layout))))
# Make each plot, in the correct location
for (i in 1:numPlots) {
# Get the i,j matrix positions of the regions that contain this subplot
matchidx <- as.data.frame(which(layout == i, arr.ind = TRUE))
print(plots[[i]], vp = viewport(layout.pos.row = matchidx$row,
layout.pos.col = matchidx$col))
}
}
}
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