Based on the answers by @James and @Jyotirmoy Bhattacharya I came up with this solution:
zx <- replicate (5, rnorm(50))
zx_means <- (colMeans(zx, na.rm = TRUE))
boxplot(zx, horizontal = FALSE, outline = FALSE)
points(zx_means, pch = 22, col = "darkgrey", lwd = 7)
(See this post for more details)
If you would like to add points to horizontal box plots, please see this post.
With ggplot2
:
p<-qplot(spray,count,data=InsectSprays,geom='boxplot')
p<-p+stat_summary(fun.y=mean,shape=1,col='red',geom='point')
print(p)
I also think chart.Boxplot is the best option, it gives you the position of the mean but if you have a matrix with returns all you need is one line of code to get all the boxplots in one graph.
Here is a small ETF portfolio example.
library(zoo)
library(PerformanceAnalytics)
library(tseries)
library(xts)
VTI.prices = get.hist.quote(instrument = "VTI", start= "2007-03-01", end="2013-03-01",
quote = c("AdjClose"),provider = "yahoo",origin ="1970-01-01",
compression = "m", retclass = c("zoo"))
VEU.prices = get.hist.quote(instrument = "VEU", start= "2007-03-01", end="2013-03-01",
quote = c("AdjClose"),provider = "yahoo",origin ="1970-01-01",
compression = "m", retclass = c("zoo"))
VWO.prices = get.hist.quote(instrument = "VWO", start= "2007-03-01", end="2013-03-01",
quote = c("AdjClose"),provider = "yahoo",origin ="1970-01-01",
compression = "m", retclass = c("zoo"))
VNQ.prices = get.hist.quote(instrument = "VNQ", start= "2007-03-01", end="2013-03-01",
quote = c("AdjClose"),provider = "yahoo",origin ="1970-01-01",
compression = "m", retclass = c("zoo"))
TLT.prices = get.hist.quote(instrument = "TLT", start= "2007-03-01", end="2013-03-01",
quote = c("AdjClose"),provider = "yahoo",origin ="1970-01-01",
compression = "m", retclass = c("zoo"))
TIP.prices = get.hist.quote(instrument = "TIP", start= "2007-03-01", end="2013-03-01",
quote = c("AdjClose"),provider = "yahoo",origin ="1970-01-01",
compression = "m", retclass = c("zoo"))
index(VTI.prices) = as.yearmon(index(VTI.prices))
index(VEU.prices) = as.yearmon(index(VEU.prices))
index(VWO.prices) = as.yearmon(index(VWO.prices))
index(VNQ.prices) = as.yearmon(index(VNQ.prices))
index(TLT.prices) = as.yearmon(index(TLT.prices))
index(TIP.prices) = as.yearmon(index(TIP.prices))
Prices.z=merge(VTI.prices, VEU.prices, VWO.prices, VNQ.prices,
TLT.prices, TIP.prices)
colnames(Prices.z) = c("VTI", "VEU", "VWO" , "VNQ", "TLT", "TIP")
returnscc.z = diff(log(Prices.z))
start(returnscc.z)
end(returnscc.z)
colnames(returnscc.z)
head(returnscc.z)
Return Matrix
ret.mat = coredata(returnscc.z)
class(ret.mat)
colnames(ret.mat)
head(ret.mat)
Box Plot of Return Matrix
chart.Boxplot(returnscc.z, names=T, horizontal=TRUE, colorset="darkgreen", as.Tufte =F,
mean.symbol = 20, median.symbol="|", main="Return Distributions Comparison",
element.color = "darkgray", outlier.symbol = 20,
xlab="Continuously Compounded Returns", sort.ascending=F)
You can try changing the mean.symbol, and remove or change the median.symbol. Hope it helped. :)
Check chart.Boxplot from package PerformanceAnalytics
. It lets you define the symbol to use for the mean of the distribution.
By default, the chart.Boxplot(data)
command adds the mean as a red circle and the median as a black line.
Here is the output with sample data; MWE:
#install.packages(PerformanceAnalytics)
library(PerformanceAnalytics)
chart.Boxplot(cars$speed)
Source: Stackoverflow.com