burgueno.alpha {agridat} | R Documentation |
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, numeric
A field experiment with 3 reps, 4 blocks per rep, laid out as an alpha design.
The plot size is not given.
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.
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)