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asreml.object – Contains a fitted linear mixed model from the asreml() function.

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 E-BLUPs 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$sigma2 and returned by the summary function.
predictions If predict is not NULL, a list object with components pvals, sed, vcov and avsed. The predictions component only is returned by the predict method for asreml objects.
fitted.values A vector containing the fitted values from the model, obtained by transforming the linear predictors by the inverse of the link function.
linear.predictors The linear fit on the link scale.
residuals A single column matrix containing the residuals from the model.
hat The diagonal elements of the matrix WC−1 W T, the extended hat matrix. This is the linear mixed effects model analogue of X(X T X) −1 X T for ordinary linear models.
sigma2 The REML estimate of the scale parameter.
deviance The deviance from the fit.
nedf The residual degrees of freedom, length(y)-rank(X).
nwv The number of working variables.
noeff A vector containing the number of effects for each term.
yssqu A vector of incremental sums of squares for (dense) fixed terms.
ai The inverse average information matrix of the variance parameters. A Matrix class object, sub-class dspMatrix.
Cfixed Reflexive generalised inverse of the coefficient matrix of the mixed model equations relating to the dense fixed effects (if asreml.options()$Cfixed=TRUE). A matrix of class Matrix, sub-class dspMatrix.
Csparse If asreml.options()$Csparse is not NULL, the non-zero elements of the reflexive generalised inverse matrix of the coefficient matrix for the sparse stored model terms nominated in the Csparse formula. A matrix in triplet form giving the row, column and non-zero element.
design The design matrix as a sparse Matrix of class dgCMatrix if asreml.options(design=TRUE).
call An image of the asreml function call.
trace A numeric matrix recording the convergence sequence for each random component, as well as the log-likelihood, residual variance and residual degrees of freedom.
license A character string containing the license information. The string has embedded new-line characters and is best formatted through cat().
G.param A list object containing the constraints and final estimates of the variance parameters relating to the random part of the model. This object may be used as the value of the G.param argument to provide initial parameter estimates to asreml.
R.param A list object containing the constraints and final estimates of the variance parameters relating to the error structure of the model. This object may be used as the value of the R.param argument to provide initial parameter estimates to asreml.
formulae A list object containing the fixed, random, sparse and residual formula arguments to asreml.
factor.names A character vector of term names appearing in the model.
meff Regressor scores (marker effects) if nominated in the mef list argument.
mf The model frame with the data as a data.table object with numerous attributes from the model specification. Inspect names(attributes(object$mf)) for details.
Updated on August 9, 2018

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