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10 Tabulation of the data and prediction from the model 167List of predict plot optionsoptionactionˆabbrdlab nˆabbrxlab nˆabbrslab nspecifies that the labels used for the data be abbreviated to ncharacters.specifies that the labels used for the x-axis annotation be appreviatedto n characters.specifies that the labels used for superimposed factors be abbreviatedto n characters.Complicated weightingNewCautionGenerally, when forming a prediction table, it is necessary to average over (orignore) some potential dimensions of the prediction table. By default, ASRemluses equal weights (1/f for a factor with f levels). More complicated weightingis achieved by using the !AVERAGE qualifier to set specific (unequal) weights foreach level of a factor. However, sometimes the weights to be used need to bedefined with respect to two or more factors. The simplest case is when there aremissing cells and weighting is equal for those cells in a multiway table that arepresent; achieved by using the !PRESENT qualifier. This is now further generalizedby allowing the user to fill in the weights for use by the !PRESENT machinery viathe !PRWTS qualifier.The user specifies the factors in the table of weights with the !PRESENT statementand then gives the table of weights using the !PRWTS qualifier. There may only beone !PRESENT qualifier on the predict line when !PRWTS is specified. The orderof factors in the tables of weights must correspond to the order in the !PRESENTlist with later factors nested within preceding factors. Check the output to ensurethat the values in the tables of weights are applied in the correct order. ASRemlmay transpose the table of weights to match the order it needs for processing.Consider a rather complicated example from a rotation experiment conductedover several years. This particular analysis followed the analysis of the daily liveweight gain per hectare of the sheep grazing the plots. There were periods whenno sheep grazed. Different flocks grazed in the different years. Daily liveweight