Mao Jianfeng
2009-Aug-24 07:40 UTC
[R] how to add 95% confidential interval as vertical lines to x axe in density plot
Dear R-help listers,
I want to add 95% confidential interval as vertical lines to x
axe in density plot. I have found the library(hdrcde) can do this
work, but I do not know
how to handle functions of this library when I used ggplot2 to draw the graph.
Thank you in advance.
The data and codes followed:
# dummy data
factor<-rep(c("Alice","Jone","Mike"),each=100)
factor<-factor(factor)
traits1<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits2<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits3<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits4<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits5<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits6<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits7<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits8<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits9<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits10<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits11<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits12<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits13<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits14<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits15<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits16<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits17<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits18<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits19<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits20<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
traits21<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
myda<-data.frame(factor,traits1,traits2,traits3,traits4,traits5,traits6,traits7,traits8,traits9,traits10,traits11,traits12,traits13,traits14,traits15,traits16,traits17,traits18,
traits19,traits20,traits21)
library(ggplot2)
d = melt(myda, id = "factor")
str(d)
pdf("test33.pdf")
p ggplot(data=d, mapping=aes(x=value, y=..density..)) +
facet_wrap(~variable)+
stat_density(aes(fill=factor), alpha=0.5, col=NA, position = 'identity')
+
stat_density(aes(colour = factor), geom="path", position =
'identity')
print(p)
dev.off()
Mao J-F
ONKELINX, Thierry
2009-Aug-24 08:35 UTC
[R] how to add 95% confidential interval as vertical lines to x axein density plot
Show us how you extract the confidence interval from the functions in
the hdrcde library and then we might be able to help you.
HTH,
Thierry
------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be
www.inbo.be
To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data.
~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey
-----Oorspronkelijk bericht-----
Van: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
Namens Mao Jianfeng
Verzonden: maandag 24 augustus 2009 9:40
Aan: r-help at r-project.org
Onderwerp: [R] how to add 95% confidential interval as vertical lines to
x axein density plot
Dear R-help listers,
I want to add 95% confidential interval as vertical lines to x axe in
density plot. I have found the library(hdrcde) can do this work, but I
do not know how to handle functions of this library when I used ggplot2
to draw the graph.
Thank you in advance.
The data and codes followed:
# dummy data
factor<-rep(c("Alice","Jone","Mike"),each=100)
factor<-factor(factor)
traits1<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6)) traits2<-c(rnorm(100, mean=1, sd=1),
rnorm(100, mean=3, sd=3), rnorm(100, mean=6, sd=6))
traits3<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6)) traits4<-c(rnorm(100, mean=1, sd=1),
rnorm(100, mean=3, sd=3), rnorm(100, mean=6, sd=6))
traits5<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6)) traits6<-c(rnorm(100, mean=1, sd=1),
rnorm(100, mean=3, sd=3), rnorm(100, mean=6, sd=6))
traits7<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6)) traits8<-c(rnorm(100, mean=1, sd=1),
rnorm(100, mean=3, sd=3), rnorm(100, mean=6, sd=6))
traits9<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6)) traits10<-c(rnorm(100, mean=1, sd=1),
rnorm(100, mean=3, sd=3), rnorm(100, mean=6, sd=6))
traits11<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6)) traits12<-c(rnorm(100, mean=1, sd=1),
rnorm(100, mean=3, sd=3), rnorm(100, mean=6, sd=6))
traits13<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6)) traits14<-c(rnorm(100, mean=1, sd=1),
rnorm(100, mean=3, sd=3), rnorm(100, mean=6, sd=6))
traits15<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6)) traits16<-c(rnorm(100, mean=1, sd=1),
rnorm(100, mean=3, sd=3), rnorm(100, mean=6, sd=6))
traits17<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6)) traits18<-c(rnorm(100, mean=1, sd=1),
rnorm(100, mean=3, sd=3), rnorm(100, mean=6, sd=6))
traits19<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6)) traits20<-c(rnorm(100, mean=1, sd=1),
rnorm(100, mean=3, sd=3), rnorm(100, mean=6, sd=6))
traits21<-c(rnorm(100, mean=1, sd=1), rnorm(100, mean=3, sd=3),
rnorm(100, mean=6, sd=6))
myda<-data.frame(factor,traits1,traits2,traits3,traits4,traits5,traits6,
traits7,traits8,traits9,traits10,traits11,traits12,traits13,traits14,tra
its15,traits16,traits17,traits18,
traits19,traits20,traits21)
library(ggplot2)
d = melt(myda, id = "factor")
str(d)
pdf("test33.pdf")
p ggplot(data=d, mapping=aes(x=value, y=..density..)) +
facet_wrap(~variable)+ stat_density(aes(fill=factor), alpha=0.5, col=NA,
position = 'identity') + stat_density(aes(colour = factor),
geom="path",
position = 'identity')
print(p)
dev.off()
Mao J-F
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