Description
asreml.object: This (S3) class object contains a ﬁtted linear mixed model from the asreml()
function. Objects of this class have methods for the generic functions wald(), coef(), fitted(), plot(), predict(), resid(), summary()
and update()
.
Value
A list object with class asreml ; the following components are included in a valid asreml object: 

loglik 
The loglikelihood at completion of the asreml call. 
vparameters 
The vector of variance parameter estimates from the ﬁt. 
vparameters.con 
A numeric vector identifying the boundary constraint applied to each variance parameter at termination. Common values are 1, 3 and 4 for Positive, Unconstrained and Fixed, respectively. The function vpc.char can be used to interpret the numeric values as per summary.asreml . 
vparameters.type 
A numeric vector identifying the variance parameter types. Numeric values are used internally and the character codes as used by the own() variance model can be obtained from the function vpt.char . 
vparameters.pc 
Percentage change in gammas on the last iteration. 
score 
The score vector of length number of random parameters. 
coefﬁcients 
A list with three components named fixed , random and sparse containing the solutions to the mixed model equations corresponding to the ﬁxed effects, the EBLUPs of the random effects, and the solutions corresponding to the sparse ﬁxed effects, respectively. The coefﬁcients are labelled by a concatenation of factor name and level separated by “_”. 
vcoeff 
A list with three components named fixed , random and sparse containing the unscaled variances of the coefﬁcients. The actual variances are calculated as vcoeff*object$sigma2 and returned by the summary function. 
predictions 
If predict is not NULL , a list object with components pvals , sed, vcov and avsed . The predictions component only is returned by the predict method for asreml objects. 
ﬁtted.values 
A vector containing the ﬁtted values from the model, obtained by transforming the linear predictors by the inverse of the link function. 
linear.predictors 
The linear ﬁt on the link scale. 
residuals 
A single column matrix containing the residuals from the model. 
hat 
The diagonal elements of the matrix WC^{−1} W ^{T}, the extended hat matrix. This is the linear mixed effects model analogue of X(X ^{T} X) ^{−1} X ^{T} for ordinary linear models. 
sigma2 
The REML estimate of the scale parameter. 
deviance 
The deviance from the ﬁt. 
nedf 
The residual degrees of freedom, length(y)rank(X) . 
nwv 
The number of working variables. 
noeff 
A vector containing the number of effects for each term. 
yssqu 
A vector of incremental sums of squares for (dense) ﬁxed terms. 
ai 
The inverse average information matrix of the variance parameters. A Matrix class object, subclass dspMatrix . 
Cﬁxed 
Reﬂexive generalised inverse of the coefﬁcient matrix of the mixed model equations relating to the dense ﬁxed effects (if asreml.options()$Cfixed=TRUE ). A matrix of class Matrix , subclass dspMatrix . 
Csparse 
If asreml.options()$Csparse is not NULL , the nonzero elements of the reﬂexive generalised inverse matrix of the coefﬁcient matrix for the sparse stored model terms nominated in the Csparse formula. A matrix in triplet form giving the row, column and nonzero element. 
design 
The design matrix as a sparse Matrix of class dgCMatrix if asreml.options(design=TRUE) . 
call 
An image of the asreml function call. 
trace 
A numeric matrix recording the convergence sequence for each random component, as well as the loglikelihood, residual variance and residual degrees of freedom. 
license 
A character string containing the license information. The string has embedded newline characters and is best formatted through cat() . 
G.param 
A list object containing the constraints and ﬁnal estimates of the variance parameters relating to the random part of the model. This object may be used as the value of the G.param argument to provide initial parameter estimates to asreml . 
R.param 
A list object containing the constraints and ﬁnal estimates of the variance parameters relating to the error structure of the model. This object may be used as the value of the R.param argument to provide initial parameter estimates to asreml . 
formulae 
A list object containing the fixed , random, sparse and residual formula arguments to asreml . 
factor.names 
A character vector of term names appearing in the model. 
meff 
Regressor scores (marker effects) if nominated in the mef list argument. 
mf 
The model frame with the data as a data.table object with numerous attributes from the model speciﬁcation. Inspect names(attributes(object$mf)) for details. 