Incomplete block alpha design
Incomplete block alpha design
data("burgueno.alpha")
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
A field experiment with 3 reps, 4 blocks per rep, laid out as an alpha design.
The plot size is not given.
Electronic version of the data obtained from CropStat software.
Used with permission of Juan Burgueno.
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
## Not run: library(agridat) data(burgueno.alpha) dat <- burgueno.alpha libs(desplot) desplot(dat, yield~col*row, out1=rep, out2=block, # aspect unknown text=gen, cex=1,shorten="none", main='burgueno.alpha') libs(lme4,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 libs(asreml) # 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 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)
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