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15 Examples 288Table 15.11 Orange data: AOV decompositionstratum decomposition type df or neconstant 1 F 1ageage F 1spl(age,7) R 5fac(age) R 7treetree RC 5age.treex.tree RC 5spl(age,7).tree R 25errorRAn extract of the ASReml input file iscirc ~ mu age !r Tree 4.6 Tree.age .000094 spl(age,7) .1,spl(age,7).Tree 2.3 fac(age) 13.90 0 1Tree 22 0 US 4.6 .00001 .0000945 0 0predict age Tree !IGNORE fac(age)We stress the importance of model building in these settings, where we generallycommence with relatively simple variance models and update to more complexvariance models if appropriate. Table 15.12 presents the sequence of fitted modelswe have used. Note that the REML log-likelihoods for models 1 and 2 arecomparable and likewise for models 3 to 6. The REML log-likelihoods are notcomparable between these groups due to the inclusion of the fixed season termin the second set of models.We begin by modelling the variance matrix for the intercept and slope for eachtree, Σ, as a diagonal matrix as there is no point including a covariance componentbetween the intercept and slope if the variance component(s) for one (orboth) is zero. Model 1 also does not include a non-smooth component at theoverall level (that is, fac(age)). Abbreviated output is shown below.