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5 Command file: Reading the data 81List of very rarely used job control qualifiersqualifieractionNewNewNew!SCALE 1!SCORE!SLOW n!TOLERANCE [s 1 [ s 2]]!VRBWhen forming a design matrix for the spl() model term,ASReml uses a standardized scale (independent of the actualscale of the variable). The qualifier !SCALE 1 forces ASRemlto use the scale of the variable. The default standardisedscale is appropriate in most circumstances.requests ASReml write the SCORE vector and the AverageInformation matrix to files basename.SCO and basename.AIM.The values written are from the last iteration.reduces the update step sizes of the variance parameters morepersistently than the !STEP r qualifier. If specified, ASRemllooks at the potential size of the updates and if any are large,it reduces the size of r. If n is greater than 10 ASReml alsomodifies the Information matrix by multiplying the diagonalelements by n. This has the effect of further reducing theupdates. This option may help when you do not have goodstarting values, especially in multivariate analyses.modifies the ability of ASReml to detect singularities in themixed model equations. This is intended for use on therare occasions when ASReml detects singularities after thefirst iteration; they are not expected. Normally (when no!TOLERANCE qualifier is specified), a singularity is declared ifthe adjusted sum of squares of a covariable is less than a smallconstant (η) or less than the uncorrected sum of squares ×η,where η is 10 −8 in the first iteration and 10 −10 thereafter.The qualifier scales η by 10 s ifor the the first or subsequentiterations respectively, so that it is more likely an equationwill be declared singular. Once a singularity is detected, thecorresponding equation is dropped (forced to be zero) in subsequentiterations. If neither argument is supplied, 2 is assumed.If the second argument is omitted, it is given thevalue of the first.If the problem of later singularities arises because of the lowcoefficient of variation of a covariable, it would be better tocentre and rescale the covariable. If the degrees of freedomare correct in the first iteration, the problem will be withthe variance parameters and a different variance model (orvariance constraints) is required.requests writing of .vrb file. Previously, the default was towrite the file.