# NOT RUN {
data(polson.safflower.uniformity)
dat <- polson.safflower.uniformity
require(desplot)
desplot(yield ~ col*row, data=dat,
flip=TRUE, aspect=189/110, # true aspect
main="polson.safflower.uniformity")
require(agricolae)
require(reshape2)
dmat <- acast(dat, row~col, value.var="yield")
# Similar to Polson fig 4.
tab <- index.smith(dmat, col="red",
main="polson.safflower.uniformity - Smith Index",
xlab="Plot size in number of basic plots")
# Polson p. 25 said CV decreased from 14.3 to 4.5
# for increase from 1 unit to 90 units. Close match.
tab <- data.frame(tab$uniformity)
# Polson only uses log(Size) < 2 in his Fig 5, obtained slope -0.63
coef(lm(log(Vx) ~ log(Size), subset(tab, Size <= 6))) # -0.70
# Polson table 2 reported labor for
# K1, number of plots, 133 hours 75<!-- % -->
# K2, size of plot, 43.5 hours 24<!-- % -->
# Optimum plot size
# X = b K1 / ((1-b) K2)
# Polson suggests optimum plot size 2.75 to 11 basic plots
# }
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