agridat (version 1.16)

reid.grasses: Yields of four grasses for a wide range of nitrogen fertilizer

Description

Yields of four grasses for a wide range of nitrogen fertilizer, conducted over 3 years.

Usage

data("reid.grasses")

Format

A data frame with 210 observations on the following 5 variables.

nitro

nitrogen, 21 numeric levels

year

Y1, Y2, or Y3

gen

genotype

drymatter

dry matter content

protein

protein content

Details

Experiment at the Hannah Research Institute, Ayr.

Single plots were planted to 4 different kinds of grasses. Within each plot, 21 nitrogen treatments were randomized.

Reid modeled the dry matter yield with four-parameter logistic curves of the form y = a - b exp(-cx^d).

References

None

Examples

# NOT RUN {
data(reid.grasses)
dat <- reid.grasses

if(require(latticeExtra)){
  foo <- xyplot(drymatter + protein ~ nitro|year, dat, group=gen,
                auto.key=list(columns=4),
                as.table=TRUE, type=c('p','l'),
                main="reid.grasses",ylab="drymatter/protein trait value",
                scales=list(y=list(relation="free")))
  combineLimits(foo)
}

# }
# NOT RUN {
  
  library(nlme)
  dat2 <- dat
  dat2$indiv <- paste(dat$year, dat$gen) # individual year+genotype curves
  
  # use all data to get initial values
  inits <- getInitial(drymatter ~ SSfpl(nitro, A, B, xmid, scal), data = dat2)
  inits
  ##         A          B       xmid       scal 
  ## -4.167902  12.139796  68.764796 128.313106 
  xvals <- 0:800
  y1 <- with(as.list(inits), SSfpl(xvals, A, B, xmid, scal))
  plot(drymatter ~ nitro, dat2)
  lines(xvals,y1)
  
  # must have groupedData object to use augPred
  dat2 <- groupedData(drymatter ~ nitro|indiv, data=dat2)
  plot(dat2)
  
  # without 'random', all effects are included in 'random'
  m1 <- nlme(drymatter ~ SSfpl(nitro, A, B, xmid,scale),
             data= dat2,
             fixed= A + B + xmid + scale ~ 1,
             # random = B ~ 1|indiv, # to make only B random
             random = A + B + xmid + scale ~ 1|indiv,
             start=inits)
  fixef(m1)
  summary(m1)
  plot(augPred(m1, level=0:1),
       main="reid.grasses - observed/predicted data",) # only works with groupedData object
  
# }
# NOT RUN {
# }