[R] Overlying a Normal Dist in a Barplot
Bret Collier
bret at tamu.edu
Fri Jul 8 21:22:14 CEST 2005
R-Users,
Hopefully someone can shed some light on these questions as I had
little luck searching the archives (although I probably missed something
in my search due to the search phrase). I estimated multinomial
probabilities for some count data (number successful offspring) ranging
from 0 to 8 (9 possible response categories). I constructed a barplot
(using barplot2) and I want to "overlay" a normal distribution on the
figure (using rnorm (1000, mean, sd)). My intent is to show that using
a mean(and associated sd) estimated from discrete count data may not be
a valid representation of the distribution of successful offspring.
Obviously the x and y axes (as structured in barplot2) will not be
equivalent for these 2 sets of information and this shows up in my
example below.
1) Is it possible to somehow reconcile the underlying x-axis to the
same scale as would be needed to overly the normal distribution (e.g.
where 2.5 would fall on the normal density, I could relate it to 2.5 on
the barplot)? Then, using axis (side=4) I assume I could insert a
y-axis for the normal distribution.
2) Is lines(density(x)) the appropriate way to insert a normal
distribution into this type of figure? Should I use 'curve'?
If someone could point me in the right direction, I would appreciate
it.
TIA, Bret
Example:
testdata
0 0.196454948
1 0.063515510
2 0.149187592
3 0.237813885
4 0.282127031
5 0.066469719
6 0.001477105
7 0.001477105
8 0.001477105
x<-rnorm(1000, 2.84, 1.57)
barplot2(testdata, xlab="Fledgling Number",
ylab="Probability", ylim=c(0, 1), col="black",
border="black", axis.lty=1)
lines(density(x))
--Version--
platform i386-pc-mingw32
arch i386
os mingw32
system i386, mingw32
status
major 2
minor 0.1
year 2004
month 11
day 15
language R
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