Hessian fly damage to wheat varieties
Hessian fly damage to wheat varieties
blockblock factor, 4 levels
genotype factor, 16 wheat varietieslatlatitude, numeric
longlongitude, numeric
ynumber of damaged plants
nnumber of total plants
The response is binomial.
Each plot was square.
C. A. Gotway and W. W. Stroup. A Generalized Linear Model Approach to Spatial Data Analysis and Prediction Journal of Agricultural, Biological, and Environmental Statistics, 2, 157-178.
https://doi.org/10.2307/1400401
The GLIMMIX procedure. https://www.ats.ucla.edu/stat/SAS/glimmix.pdf
## Not run:
library(agridat)
data(gotway.hessianfly)
dat <- gotway.hessianfly
dat$prop <- dat$y / dat$n
libs(desplot)
desplot(dat, prop~long*lat,
aspect=1, # true aspect
out1=block, num=gen, cex=.75,
main="gotway.hessianfly")
# ----------------------------------------------------------------------------
# spaMM package example
libs(spaMM)
m1 = HLCor(cbind(y, n-y) ~ 1 + gen + (1|block) + Matern(1|long+lat),
data=dat, family=binomial(), ranPars=list(nu=0.5, rho=1/.7))
summary(m1)
fixef(m1)
# The following line fails with "Invalid graphics state"
# when trying to use pkgdown::build_site
# filled.mapMM(m1)
# ----------------------------------------------------------------------------
# Block random. See Glimmix manual, output 1.18.
# Note: (Different parameterization)
libs(lme4)
l2 <- glmer(cbind(y, n-y) ~ gen + (1|block), data=dat, family=binomial,
control=glmerControl(check.nlev.gtr.1="ignore"))
coef(l2)
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