Slate Hall Farm 1978 — gilmour.slatehall • agridat

Yields for a trial at Slate Hall Farm in 1978.

Format

A data frame with 150 observations on the following 5 variables.

row: row
col: column
yield: yield (grams/plot)
gen: genotype factor, 25 levels
rep: rep factor, 6 levels

Details

The trial was of spring wheat at Slate Hall Farm in 1978. The experiment was a balanced lattice with 25 varieties in 6 replicates. The 'rep' labels are arbitrary (no rep labels appeared in the source data). Each row within a rep is an incomplete block. The plot size was 1.5 meters by 4 meters.

Field width: 10 plots x 4 m = 40 m

Field length: 15 plots x 1.5 meters = 22.5 m

Source

Arthur R Gilmour and Brian R Cullis and Arunas P Verbyla (1997). Accounting for natural and extraneous variation in the analysis of field experiments. Journal of Agricultural, Biological, and Environmental Statistics, 2, 269-293. https://doi.org/10.2307/1400446

References

None.

Examples

# \dontrun{

  library(agridat)
  data(gilmour.slatehall)
  dat <- gilmour.slatehall

  libs(desplot)
  desplot(dat, yield ~ col * row,
          aspect=22.5/40, num=gen, out1=rep, cex=1,
          main="gilmour.slatehall")

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

  libs(asreml,lucid) # asreml4

  # Model 4 of Gilmour et al 1997
  dat <- transform(dat, xf=factor(col), yf=factor(row))
  dat <- dat[order(dat$xf, dat$yf), ]
  m4 <- asreml(yield ~ gen + lin(row), data=dat,
               random = ~ dev(row) + dev(col),
               resid = ~ ar1(xf):ar1(yf))
#> Model fitted using the gamma parameterization.
#> ASReml 4.1.0 Mon Jan 11 17:08:41 2021
#>           LogLik        Sigma2     DF     wall    cpu
#>  1      -733.509      30064.20    124 17:08:41    0.0
#>  2      -725.011      26801.71    124 17:08:41    0.0
#>  3      -718.953      25508.52    124 17:08:41    0.0
#>  4      -716.764      24942.33    124 17:08:41    0.0
#>  5      -716.202      24265.54    124 17:08:41    0.0
#>  6      -716.167      23974.18    124 17:08:41    0.0
#>  7      -716.166      23946.12    124 17:08:41    0.0
  # coef(m4)$fixed[1] # linear row
  # [1] 31.72252 # (sign switch due to row ordering)

  vc(m4)
#>        effect component std.error z.ratio bound %ch
#>      dev(col)  2519      1959         1.3     P   0
#>      dev(row) 20290     10260         2       P   0
#>       xf:yf!R 23950      4616         5.2     P   0
#>  xf:yf!xf!cor     0.439     0.113     3.9     U   0
#>  xf:yf!yf!cor     0.125     0.117     1.1     U   0
  ##       effect component std.error z.ratio bound 
  ##     dev(col)  2519      1959         1.3     P   0
  ##     dev(row) 20290     10260         2       P   0
  ##     xf:yf(R) 23950      4616         5.2     P   0
  ## xf:yf!xf!cor     0.439     0.113     3.9     U   0
  ## xf:yf!yf!cor     0.125     0.117     1.1     U   0
  
  plot(varioGram(m4), main="gilmour.slatehall")

# }