mercer.wheat.uniformity | R Documentation |
Uniformity trial of wheat at Rothamsted Experiment Station, England, 1910.
A data frame with 500 observations on the following 4 variables.
row
row
col
column
grain
grain yield, pounds
straw
straw yield, pounds
The wheat crop was grown in the summer of 1910 at Rothamsted Experiment Station (Harpenden, Hertfordshire, England). In the Great Knott, a seemingly uniform area of 1 acre was harvested in separate plots, each 1/500th acre in size. The grain and straw from each plot was weighed separately.
McCullagh gives more information about the plot size.
Field width: 25 plots * 8 ft = 200 ft
Field length: 20 plots * 10.82 ft = 216 ft
D. G. Rossiter (2014) uses this data for an extensive data analysis tutorial.
Mercer, WB and Hall, AD, (1911). The experimental error of field trials The Journal of Agricultural Science, 4, 107-132. Table 5. https://doi.org/10.1017/S002185960000160X
McCullagh, P. and Clifford, D., (2006). Evidence for conformal invariance of crop yields, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Science, 462, 2119–2143. https://doi.org/10.1098/rspa.2006.1667
Theodor Roemer (1920). Der Feldversuch. Page 65, table 6.
D. G. Rossiter (2014). Tutorial: Using the R Environment for Statistical Computing An example with the Mercer & Hall wheat yield dataset.
G. A. Baker (1941). Fundamental Distribution of Errors for Agricultural Field Trials. National Mathematics Magazine, 16, 7-19. https://doi.org/10.2307/3028105
The 'spdep' package includes the grain yields (only) and spatial positions of plot centres in its example dataset 'wheat'.
Note, checked that all '4.03' values in this data match the original document.
## Not run:
library(agridat)
data(mercer.wheat.uniformity)
dat <- mercer.wheat.uniformity
libs(desplot)
desplot(dat, grain ~ col*row,
aspect=216/200, # true aspect
main="mercer.wheat.uniformity - grain yield")
libs(lattice)
xyplot(straw ~ grain, data=dat, type=c('p','r'),
main="mercer.wheat.uniformity - regression")
libs(hexbin)
hexbinplot(straw ~ grain, data=dat)
libs(sp, gstat)
plot.wid <- 2.5
plot.len <- 3.2
nr <- length(unique(dat$row))
nc <- length(unique(dat$col))
xy <- expand.grid(x = seq(plot.wid/2, by=plot.wid, length=nc),
y = seq(plot.len/2, by=plot.len, length=nr))
dat.sp <- dat
coordinates(dat.sp) <- xy
# heatmap
spplot(dat.sp, zcol = "grain", cuts=8,
cex = 1.6,
col.regions = bpy.colors(8),
main = "Grain yield", key.space = "right")
# variogram
# Need gstat::variogram to get the right method
vg <- gstat::variogram(grain ~ 1, dat.sp, cutoff = plot.wid * 10, width = plot.wid)
plot(vg, plot.numbers = TRUE,
main="mercer.wheat.uniformity - variogram")
## End(Not run)
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