if (FALSE) {
library(agridat)
data(lessman.sorghum.uniformity)
dat <- lessman.sorghum.uniformity
libs(desplot)
desplot(dat, yield ~ col*row,
aspect=300/160, tick=TRUE, flip=TRUE, # true aspect
main="lessman.sorghum.uniformity")
# Omit outer two columns (called 'rows' by Lessman)
dat <- subset(dat, col > 2 & col < 47)
nrow(dat)
var(dat$yield) # 9.09
sd(dat$yield)/mean(dat$yield) # CV 9.2
libs(reshape2)
libs(agricolae)
dmat <- acast(dat, row~col, value.var='yield')
index.smith(dmat,
main="lessman.sorghum.uniformity",
col="red") # Similar to Lessman Table 1
# Lessman said that varying the width of plots did not have an appreciable
# effect on CV, and optimal row length was 3.2 basic plots, about 15-20
}
Run the code above in your browser using DataLab