agridat (version 1.8.1)

theobald.covariate: Silage yields for Year * Loc * Variety with covariate

Description

Silage yields for maize in 5 years at 7 districts for 10 hybrids.

source

Chris M. Theobald and Mike Talbot and Fabian Nabugoomu, 2002. A Bayesian Approach to Regional and Local-Area Prediction From Crop Variety Trials, Journ Agric Biol Env Sciences, 7, 403--419.

Details

The trials were carried out in seven districts in the maritime provinces of Eastern Canada. Different fields were used in successive years. The covariate CHU (Corn Heat Units) is the accumulated average daily temperatures (thousands of degrees Celsius) during the growing season at each location. Thanks to Chris Theobald for permission to use the data and for BUGS code.

Examples

theo <- theobald.covariate

# REML estimates (Means) in table 3 of Theobald 2002
require("lme4")
theo <- transform(theo, year=factor(year))
m0 <- lmer(yield ~ -1 + gen + (1|year/env) + (1|gen:year), data=theo)
round(fixef(m0),2)

# Use JAGS to fit Theobald (2002) model 3.2 with 'Expert' prior

require("reshape2")
ymat <- acast(theo, year+env~gen, value.var='yield')
chu <- acast(theo, year+env~., mean, value.var='chu', na.rm=TRUE)
chu <- as.vector(chu - mean(chu))  # Center the covariate
theo$yr <- as.numeric(theo$year)
yridx <- as.vector(acast(theo, year+env~., mean, value.var='yr', na.rm=TRUE))
theo$loc <- as.numeric(theo$env)
locidx <- acast(theo, year+env~., mean, value.var='loc', na.rm=TRUE)
locidx <- as.vector(locidx)

jdat <- list(nVar = 10, nYear = 5, nLoc = 7, nYL = 29, yield = ymat,
            chu = chu, year = yridx, loc = locidx)

require(rjags)
m1 <- jags.model(file=system.file("/files/theobald.bug", package="agridat"),
  data=jdat, n.chains=2)

# Table 3, Variety deviations from means (Expert prior)
c1 <- coda.samples(m1, variable.names=(c('alpha')),
                   n.iter=10000, thin=10)
s1 <- summary(c1)
effs <- s1$statistics[,'Mean']
rev(sort(round(effs - mean(effs), 2))) # Perfect match (different order?)