gotway.hessianfly {agridat} | R Documentation

## Hessian fly damage to wheat varieties

### Description

Hessian fly damage to wheat varieties

### Format

`block`

  block factor, 4 levels

`genotype factor, 16 wheat varieties`
`lat`

  latitude, numeric

`long`

  longitude, numeric

`y`

  number of damaged plants

`n`

  number of total plants

### Details

The response is binomial.

Each plot was square.

### Source

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.

http://doi.org/10.2307/1400401

### References

The GLIMMIX procedure. http://www.ats.ucla.edu/stat/SAS/glimmix.pdf

### Examples

    ## FIXME Could the spaMM package be useful here...????

    data(gotway.hessianfly)
    dat <- gotway.hessianfly

    dat$prop <- dat$y / dat$n
    if(require(desplot)){
      desplot(prop~long*lat, dat,
              aspect=1, # true aspect
              out1=block, text=gen, cex=1, shorten='no',
              main="gotway.hessianfly")
    }

    # ----------------------------------------------------------------------------

    # Block random.  See Glimmix manual, output 1.18.
    # Note: (Different parameterization)
    ## Not run:
      ## require(lme4)
      ## l2 <- glmer(cbind(y, n-y) ~ gen + (1|block), data=dat, family=binomial,
      ##    control=glmerControl(check.nlev.gtr.1="ignore"))
      ## coef(l2)

    ## End(Not run)

    # ----------------------------------------------------------------------------

    ## Not run:
      # asreml3
      require(asreml)
      a2 <- asreml(prop ~ gen, data=dat, random=~block,
                   family=asreml.binomial(),
                   weights=n)
      coef(a2)

    ## End(Not run)

    # ----------------------------------------------------------------------------

    ## Not run:
      ## require(asreml4)
      ## a2 <- asreml(prop ~ gen, data=dat, random=~block,
      ##              family=asr_binomial(),
      ##              weights=n)
      ## coef(a2)

    ## End(Not run)

[Package agridat version 1.16 Index]