agridat (version 1.12)

yang.barley: Yield of 6 barley varieties at 18 locations in Alberta.

Description

Yield of 6 barley varieties at 18 locations in Alberta.

Usage

data(yang.barley)

Format

A data frame with 108 observations on the following 3 variables.

site

site factor, 18 levels

gen

genotype factor, 6 levels

yield

yield, Mg/ha

Details

From an experiment in 2003. Yang (2013) uses this data to illustrate a procedure for bootstrapping biplots.

site	long	lat
Beaverlodge	119.43	55.21
BigLakes	113.70	53.61
Calmar	113.85	53.26
CdcNorth	113.33	53.63
DawsonCreek	120.23	55.76
FtKent	110.61	54.31
FtStJohn	120.85	56.25
Irricana	113.60	51.32
Killam	111.85	52.78
Lacombe	113.73	52.46
LethbridgeDry	112.81	49.70
LethbridgeIrr	112.81	49.70
Lomond	112.65	50.35
Neapolis	113.86	51.65
NorthernSunrise	NA	NA
Olds	114.09	51.78
StPaul	111.28	53.98
Stettler	112.71	52.31

References

Zhiqiu Hu and Rong-Cai Yang, (2013). Improved Statistical Inference for Graphical Description and Interpretation of Genotype x Environment Interaction. Crop Science, 53, 2400-2410.

Examples

# NOT RUN {
data(yang.barley)
dat <- yang.barley
  require(reshape2)
  dat <- acast(dat, gen~site, value.var='yield')

# }
# NOT RUN {
  ## For bootstrapping of a biplot, see the 'bbplot' and
  ## distfree.cr packages here:
  ## http://statgen.ualberta.ca/index.html?open=software.html

  require(SDMTools)
  require(distfree.cr)
  require(bbplot)

  d1 <- bbplot.boot(dat, nsample=2000) # bootstrap the data
  plot(d1) # plot distributions of principal components
  b1 <- bbplot(d1) # create data structures for the biplot
  plot(b1) # create the confidence regions on the biplot
  # this may not be working...
# }
# NOT RUN {
# }