yang.barley.Rd
Yield of 6 barley varieties at 18 locations in Alberta.
data("yang.barley")
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
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 |
Used with permission of Rong-Cai Yang.
Rong-Cai Yang (2007). Mixed-Model Analysis of Crossover Genotype-Environment Interactions. Crop Science, 47, 1051-1062. https://doi.org/10.2135/cropsci2006.09.0611
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. https://doi.org/10.2135/cropsci2013.04.0218
# \dontrun{ library(agridat) data(yang.barley) dat <- yang.barley libs(reshape2) dat <- acast(dat, gen~site, value.var='yield') ## For bootstrapping of a biplot, see the non-cran packages: ## 'bbplot' and 'distfree.cr' ## https://statgen.ualberta.ca/index.html?open=software.html ## install.packages("https://statgen.ualberta.ca/download/software/bbplot_1.0.zip") ## install.packages("https://statgen.ualberta.ca/download/software/distfree.cr_1.5.zip") ## libs(SDMTools) ## libs(distfree.cr) ## libs(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 # }