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5 Command file: Reading the data 74List of rarely used job control qualifiersqualifieractionNewCaution!EMFLAG n!PXEM nrequests ASReml use Expectation-Maximization (EM) ratherthan Average Information (AI) updates when the AI updateswould make a US structure non-positive definite. This onlyapplies to US structures and is still under development. When!GP is associated with a US structure, ASReml checks whetherthe updated matrix is positive definite (PD). If not, it replacesthe AI update with an EM update. If the non PDcharacteristic is transitory, then the EM update is only usedas necessary. If the converged solution would be non PD,there will be a EM update each iteration even though !EM isomitted.EM is notoriously slow at finding the solution and ASRemlincludes several modified schemes, discussed by Cullis et al.(2004), particularly relevant when the AI update is consistentlyoutside the parameter space. These include optionallyperforming extra local EM or PXEM (Parameter ExtendedEM) iterates. These can dramatically reduce the number ofiterates required to find a solution near the boundary of theparameter space but do not always work well when there areseveral matrices on the boundary. The options are!EMFLAG [1] Standard EM plus 10 local EM steps!EMFLAG 2 Standard EM plus 10 local PXEM steps!PXEM [2] Standard EM plus 10 local PXEM steps!EMFLAG 3 Standard EM plus 10 local EM steps!EMFLAG 4 Standard EM plus 10 local EM steps!EMFLAG 5 Standard EM only!EMFLAG 6 Single local PXEM!EMFLAG 7 Standard EM plus 1 local EM step!EMFLAG 8 Standard EM plus 10 local EM stepsOptions 3 and 4 cause all US structures to be updated by(PX)EM if any particular one requires EM updates.The test of whether the AI updated matrix is positive definititeis based on absorbing the matrix to check all pivots arepositive. Repeated EM updates may bring the matrix closerto being singular. This is assessed by dividing the pivot ofthe first element with the first diagonal element of the matrix.If it is less than 10 − 7 (this value is consistent withthe multiple partial correlation of the first variable with therest being greater than 0.9999999, ASReml fixes the matrixat that point and estimates any other parameters conditionalon these values. To preceed with further iterations withoutfixing the matrix values would ultimately make the matrixsuch that it would be judged singular resulting the analysisbeing aborted.