denis.missing {agridat} | R Documentation

## Multi-environment trial with structured missing values

### Description

Grain yield was measured on 5 genotypes in 26 environments. Missing values were non-random, but structured.

### Format

`env`

  environment, 26 levels

`gen`

  genotype factor, 5 levels

`yield`

  yield

### Source

Denis, J. B. and C P Baril, 1992, Sophisticated models with numerous missing values: The multiplicative interaction model as an example. Biul. Oceny Odmian, 24–25, 7–31.

Used with permission of Jean-Baptists Denis.

### References

H P Piepho, (1999) Stability analysis using the SAS system, Agron Journal, 91, 154–160. http://doi.og/10.2134/agronj1999.00021962009100010024x

### Examples

    data(denis.missing)
    dat <- denis.missing

    # view missingness structure
    if(require(reshape2)){
      acast(dat, env~gen, value.var='yield')
    }

    require(lattice)
    redblue <- colorRampPalette(c("firebrick", "lightgray", "#375997"))
    levelplot(yield ~ gen*env, data=dat,
              col.regions=redblue,
              main="denis.missing - incidence heatmap")

    # stability variance (Table 3 in Piepho)
    require("nlme")
    m1 <- lme(yield ~ -1 + gen, data=dat, random= ~ 1|env,
              weights = varIdent(form= ~ 1|gen),
              na.action=na.omit)
    svar <- m1$sigma^2 * c(1, coef(m1$modelStruct$varStruct, unc = FALSE))^2
    round(svar, 2)
    ##          G5    G3    G1    G2
    ## 39.25 22.95 54.36 12.17 23.77

    # m2 <- asreml(yield ~ gen, random = ~ env + at(gen):env, data=dat)

[Package agridat version 1.16 Index]