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7 Command file: Specifying variance structures 135See Sections 2.1and 7.5A summary of the rules is as follows:• when combining variance models in both Rand G structures, the resulting direct productstructure must match the ordered effectswith the outer factor first, for example,the G structure in the example opposite isfor column.row which tells ASReml that thedirect product structure matches the effectsordered rows within columns. (The variancemodel can be written as σ 2 (I +Σ C ⊗λΣ R ).)This is why the G structure definition linefor column is specified first,NIN Alliance Trial 1989variety !Aid.row 22column 11nin89.asd !skip 1yield ∼ mu variety !r repl,column.row0 0 1column.row 2column 0 AR1 0.4row 0 ARV1 0.3 0.1• ASReml automatically includes and estimates an error variance parameter foreach section of an R structure. The variance structures defined by the usershould therefore normally be correlation matrices. A variance model can bespecified but the !S2==1 qualifier would then be required to fix the error varianceat 1 and prevent ASReml trying to estimate two confounded parameters(error variance and the parameter corresponding to the variance model specified,see 3a on page 111),• ASReml does not have an implicit scale parameter for G structures that aredefined explicitly. For this reason the model supplied when the G structureinvolves just one variance model must be a variance model; an initial valuemust be supplied for this associated scale parameter; this is discussed underadditional initial values on page 119,• when the G structure involves more than one variance model, one must beeither a homogeneous or a heterogeneous variance model and the rest shouldbe correlation models; if more than one are non-correlation models then the!GF qualifier should be used to avoid identifiability problems, that is, ASRemltrying to estimate both parameters when they are confounded.7.8 G structures involving more than one random termThe usual case is that a variance structure applies to a particular term in thelinear model and that there is no covariance between model terms. Sometimes itis appropriate to include a covariance. Then, it is essential that the model termsbe listed together and that the variance structure defined for the first term be thestructure required for both terms. When the terms are of different size, the termsmust be linked together with the !{ and !} qualifiers (Table 6.1). While ASReml