# I have some population estimates and confidence intervals for various
size classes
# of animals captured with two gear types. I'd like to plot the
estimates along with
# the 90 and 95% CI's by size class for each gear type.
# The data can be read in as:
estimates <-
c(67.42,30.49,32.95,23.53,10.26,6.03,23.53,0.93,50.72,24.2,25.84,18.54,
7.16,3.6,9.35,0.33,87.28,37.25,40.16,28.59,13.77,8.92,40.74,1.68,48.28,2
3.09,
24.49,17.7,6.63,3.28,7.79,0.26,91.63,38.74,41.6,29.74,14.49,9.51,44.16,1
.88)
estimates.m<- matrix(estimates, 8,5)
colnames(estimates.m) <- list("est","lci90","uci90","lci95","uci95")
id <- c(1,1,2,2,3,3,4,4)
size <- c("All","All","Large","Large","Medium","Medium","Small","Small")
gear <- rep(c("Camera","Dredge"),4)
cds.est <- data.frame(id,size,gear,estimates.m)
# The following script works fine for plotting one size class at a time
using dotplot() and is how I
# would like the plots to look
library(lattice)
dat1 <- cds.est[cds.est$id == 1,]
dotplot(gear ~ est , data=dat1, xlim = c(min(dat1$lci95 -10),
max(dat1$uci95 +10)), xlab='Density (num / Nmi^2)',
main = as.vector(unique(dat1$size)),
panel=function(x,y) {
panel.xyplot(x,y,pch=16,cex=1)
panel.segments(dat1$lci95,as.numeric(y),dat1$uci95,as.numeric(y), lty=1,
col=1)
panel.segments(dat1$lci90,as.numeric(y),dat1$uci90,as.numeric(y), lty=1,
lwd=4, col='grey60')
panel.xyplot(x,y,pch=16,cex=1.2,col='white')
panel.xyplot(x,y,pch=1,cex=1.1,
col='black')
})
# Since I have multiple size classes and will producing similar plots
for other data sets
# I've written the following script using a loop. The script loops over
the "id" variable in the
# cds.est data frame and stores the plots in a list. Since dotplot() is
part of the
# lattice package, I used grid.arrange to tile the plots.
library(grid)
library(gridExtra)
id2 <- 1:max(cds.est$id)
plots <- vector("list", length(id2))
j <- 0
for (i in id2) {
dat <- cds.est[cds.est$id == i,]
plots[[ j <- j+1]] <-
dotplot(gear ~ est , data=dat, xlim = c(min(dat$lci95
-10), max(dat$uci95 +10)), xlab='Density (num / Nmi^2)',
main = as.vector(unique(dat$size)),
panel=function(x,y) {
panel.xyplot(x,y,pch=16,cex=1)
panel.segments(dat$lci95,as.numeric(y),dat$uci95,as.numeric(y), lty=1,
col=1)
panel.segments(dat$lci90,as.numeric(y),dat$uci90,as.numeric(y), lty=1,
lwd=4, col='grey60')
panel.xyplot(x,y,pch=16,cex=1.2,col='white')
panel.xyplot(x,y,pch=1,cex=1.1,
col='black')
})
}
do.call(grid.arrange, plots)
# The script runs and produces all the plots with the correct estimates,
but the CI's are not
# plotting correctly. Does anyone have suggestions on what is causing
this?
Thanks, Mike
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