ASReml-S reference manual - VSN International

7.3 Methods and related functions 72pseudo analysis of variance table is returned based on incremental sums of squares withrows corresponding to each of the fixed terms in the object, plus an additional row forthe residuals. The model sum of squares is partitioned into its fixed term components,and the sum of squares for each term listed in the table is adjusted for the terms listedin the rows above. The denominator degrees of freedom are not computed.If either denDF or ssType are not set at their default values, a data frame is returned thatwill include columns for the approximate denominator degrees of freedom and incrementaland conditional F statistics depending on the combination of options chosen.The principle used in determining the conditional tests is that a term cannot be adjustedfor another term which encompasses it explicitly (for example, A:C cannot be adjustedfor A:B:C or implicitly (for example, REGION¡ cannot be adjusted for LOCATION whenlocations are nested in regions although coded independently).The numerator degrees of freedom for each term is determinaed as the number of nonsingularequations involved in the term. However, the calculation of the denominator dfis in general not trivial and is computationally expensive. Numerical derivatives requirean extra evaluation of the mixed model equations for every variance parameter whilealgebraic derivatives require a large dense matrix, potentially of order the number ofequations plus the number of observations. The calculations are supressed by default.7.3.2 coef.asremlUsagecoef(object)Required argumentsobject an asreml object.Valuea list of length 3 with the following components:fixed Generalised least squares estimates for fixed terms in the model.randomsparseBLUPs from the random part of the modelGeneralised least squares estimates for fixed terms in the model thatwere included in the sparse section.7.3.3 fitted.asremlUsagefitted(object, type = c(”response”, ”link”))Required argumentsobject an asreml object.Optional argumentstype fitted values on the scale of the response (default) or link functionValuevector of fitted values.