ASReml-S reference manual - VSN International

maxiter maximum number of iterations (default is 10).stepsizeworkspacepworkspaceValueupdate shrinkage factor.7.2 The asreml object 70size of workspace for the REML routines measured in double precision words(groups of 8 bytes). The default is workspace=4e6 (or 32,000,000 bytes).size of workspace for forming predictions of linear functions of variables inthe model, measured in double precision words (groups of 8 bytes). Thedefault is workspace=4e6 (or 32,000,000 bytes).a list is returned to supply the control argument(s) to asreml. The values in asreml.control()can be supplied directly in a call to asreml; these values are filtered throughasreml.control() inside asreml.7.2 The asreml objectThe asreml class has methods for the following generic functions: coef(), fitted(), predict(),plot(), residuals() and summary(). A generic function wald() for significance testsusing Wald statistics has been defined with a method for asreml objects The followingcomponents are included in a valid asreml object.componentmonitorloglikgammasgammas.conscorecoefficientsvcoefffitted.valueslinear.predictorsresidualshatsigma2nedfaidescriptiona data frame of random components (rows) by iterations (columns)tracing the convergence sequence.the REML log-likelihood at termination.the vector of variance parameter estimates.the vector of boundary constraints applied the variance parameters(Positive, Fixed, Unconstrained)the score vector of length length(gammas).a list with three components, fixed, random and sparse, where the firstis a vector containing the estimated coefficients for the fixed effects,the second is a vector containing the estimated BLUPs for the randomeffects and the third is a vector containing the coefficients of absorbedfixed effects. The names of the coefficients are the same as those inthe formulae of the call to asreml.a list with three components, fixed, random and sparse, containingthe unscaled variances of the coefficients. The actual variances arecalculated as vcoeff*sigma2the vector of fitted values.the linear fit, given by the product of the model matrix and thecoefficients.the vector of residuals.the diagonal elements of the hat matrix.the residual variancethe residual degrees of freedoma vector of length ngamma(ngamma+1)/2 containing the lower trianglerow-wise of the inverse average information matrix on varianceparameters.