burgueno.alpha {agridat} | R Documentation

## Incomplete block alpha design

### Description

Incomplete block alpha design

### Usage

    data("burgueno.alpha")

### Format

A data frame with 48 observations on the following 6 variables.

`rep`

  rep, 3 levels

`block`

  block, 12 levels

`row`

  row

`col`

  column

`gen`

  genotype, 16 levels

`yield`

  yield, numeric

### Details

A field experiment with 3 reps, 4 blocks per rep, laid out as an alpha design.

The plot size is not given.

### Source

J Burgueno, A Cadena, J Crossa, M Banziger, A Gilmour, B Cullis. 2000. User's guide for spatial analysis of field variety trials using ASREML. CIMMYT. https://books.google.com/books?id=PR_tYCFyLCYC&pg=PA1

Electronic version of the data obtained from CropStat software.

Used with permission of Juan Burgueno.

### Examples

    data(burgueno.alpha)
    dat <- burgueno.alpha

    if(require(desplot)){
      desplot(yield~col*row, dat,
              out1=rep, out2=block, # aspect unknown
              text=gen, cex=1,shorten="none",
              main='burgueno.alpha')
    }

    ## Not run:
      require(lme4)
      require(lucid)
      # Inc block model
      m0 <- lmer(yield ~ gen + (1|rep/block), data=dat)
      vc(m0) # Matches Burgueno p. 26
      ##        grp        var1 var2   vcov sdcor
      ##  block:rep (Intercept) <NA>  86900 294.8
      ##        rep (Intercept) <NA> 200900 448.2
      ##   Residual        <NA> <NA> 133200 365

    ## End(Not run)

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

    ## Not run:
      # asreml3
      require(asreml)

      dat <- transform(dat, xf=factor(col), yf=factor(row))
      dat <- dat[order(dat$xf, dat$yf),]

      # Sequence of models on page 36

      m1 <- asreml(yield ~  gen, data=dat)
      m1$loglik # -232.13

      m2 <- asreml(yield ~  gen, data=dat,
                   random = ~ rep)
      m2$loglik # -223.48

      # Inc Block model
      m3 <- asreml(yield ~  gen, data=dat,
                   random = ~ rep/block)
      m3$loglik # -221.42
      m3$coef$fixed # Matches solution on p. 27

      # AR1xAR1 model
      m4 <- asreml(yield ~ 1 + gen, data=dat,
                   rcov = ~ar1(xf):ar1(yf))
      m4$loglik # -221.47
      plot(variogram(m4), main="burgueno.alpha") # Figure 1

      m5 <- asreml(yield ~ 1 + gen, data=dat,
                   random= ~ yf, rcov = ~ar1(xf):ar1(yf))
      m5$loglik # -220.07

      m6 <- asreml(yield ~ 1 + gen + pol(yf,-2), data=dat,
                   rcov = ~ar1(xf):ar1(yf))
      m6$loglik # -204.64 vs. 203.69

      m7 <- asreml(yield ~ 1 + gen + lin(yf), data=dat,
                   random= ~ spl(yf), rcov = ~ar1(xf):ar1(yf))
      m7$loglik # -212.51

      m8 <- asreml(yield ~ 1 + gen + lin(yf), data=dat,
                   random= ~ spl(yf))
      m8$loglik # -213.91

      # Polynomial model with predictions
      m9 <- asreml(yield ~ 1 + gen + pol(yf,-2) + pol(xf,-2), data=dat,
                   random= ~ spl(yf),  rcov = ~ar1(xf):ar1(yf))
      m9$loglik # -191.44 vs -189.61
      #p9 <- predict(m9, classify="gen:xf:yf", levels=list(xf=1,yf=1))
      #p9$predictions

      m10 <- asreml(yield ~ 1 + gen + lin(yf)+lin(xf), data=dat,
                    rcov = ~ar1(xf):ar1(yf))
      m10$loglik # -211.56

      m11 <- asreml(yield ~ 1 + gen + lin(yf)+lin(xf), data=dat,
                    random= ~ spl(yf), rcov = ~ar1(xf):ar1(yf))
      m11$loglik # -208.90

      m12 <- asreml(yield ~ 1 + gen + lin(yf)+lin(xf), data=dat,
                    random= ~ spl(yf)+spl(xf), rcov = ~ar1(xf):ar1(yf))
      m12$loglik # -206.82

      m13 <- asreml(yield ~ 1 + gen + lin(yf)+lin(xf), data=dat,
                    random= ~ spl(yf)+spl(xf))
      m13$loglik # -207.52

    ## End(Not run)

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

    ## Not run:
      ## require(asreml4)

      ## dat <- transform(dat, xf=factor(col), yf=factor(row))
      ## dat <- dat[order(dat$xf, dat$yf),]

      ## # Sequence of models on page 36

      ## m1 <- asreml(yield ~  gen, data=dat)
      ## m1$loglik # -232.13

      ## m2 <- asreml(yield ~  gen, data=dat,
      ##              random = ~ rep)
      ## m2$loglik # -223.48

      ## # Inc Block model
      ## m3 <- asreml(yield ~  gen, data=dat,
      ##              random = ~ rep/block)
      ## m3$loglik # -221.42
      ## m3$coef$fixed # Matches solution on p. 27

      ## # AR1xAR1 model
      ## m4 <- asreml(yield ~ 1 + gen, data=dat,
      ##              resid = ~ar1(xf):ar1(yf))
      ## m4$loglik # -221.47
      ## plot(varioGram(m4), main="burgueno.alpha") # Figure 1

      ## m5 <- asreml(yield ~ 1 + gen, data=dat,
      ##              random= ~ yf, resid = ~ar1(xf):ar1(yf))
      ## m5$loglik # -220.07

      ## m6 <- asreml(yield ~ 1 + gen + pol(yf,-2), data=dat,
      ##              resid = ~ar1(xf):ar1(yf))
      ## m6$loglik # -204.64 vs. 203.69

      ## m7 <- asreml(yield ~ 1 + gen + lin(yf), data=dat,
      ##              random= ~ spl(yf), resid = ~ar1(xf):ar1(yf))
      ## m7$loglik # -212.51

      ## m8 <- asreml(yield ~ 1 + gen + lin(yf), data=dat,
      ##              random= ~ spl(yf))
      ## m8$loglik # -213.91

      ## # Polynomial model with predictions
      ## m9 <- asreml(yield ~ 1 + gen + pol(yf,-2) + pol(xf,-2), data=dat,
      ##              random= ~ spl(yf),
      ##              resid = ~ar1(xf):ar1(yf))
      ## m9 <- update(m9)
      ## m9$loglik # -191.44 vs -189.61
      ## p9 <- predict(m9, classify="gen:xf:yf", levels=list(xf=1,yf=1))
      ## p9

      ## m10 <- asreml(yield ~ 1 + gen + lin(yf)+lin(xf), data=dat,
      ##               resid = ~ar1(xf):ar1(yf))
      ## m10$loglik # -211.56

      ## m11 <- asreml(yield ~ 1 + gen + lin(yf)+lin(xf), data=dat,
      ##               random= ~ spl(yf),
      ##               resid = ~ar1(xf):ar1(yf))
      ## m11$loglik # -208.90

      ## m12 <- asreml(yield ~ 1 + gen + lin(yf)+lin(xf), data=dat,
      ##               random= ~ spl(yf)+spl(xf),
      ##               resid = ~ar1(xf):ar1(yf))
      ## m12$loglik # -206.82

      ## m13 <- asreml(yield ~ 1 + gen + lin(yf)+lin(xf), data=dat,
      ##               random= ~ spl(yf)+spl(xf))
      ## m13$loglik # -207.52

    ## End(Not run)

[Package agridat version 1.16 Index]