asreml.object | R Documentation

## asreml object

### Description

This class of object represents a fitted linear mixed model from the `asreml()` function. Objects of this class have methods for the generic functions `wald(), coef(), fitted(), plot(), predict(), residuals()`, `summary()` and `update`.

### Value

The following components must be included in a legitimate asreml object. The residuals, fitted values and coefficients can be extracted by the generic functions of the same name, or by the "\$" operator.

`monitor` | a data frame of random components (rows) by iterations (columns) tracing the convergence sequence.
`loglik` | the loglikelihood at termination.
`gammas` | a vector of nk variance parameter estimates from the fit.
`gammas.con` | a vector identifying the boundary constraint applied to each variance parameter (Positive, Fixed, Unconstrained).
`score` | the score vector of length number of random components.
`coefficients` | a list with three components, `fixed, random` and `sparse`, where the first is a vector containing the E-solutions to the mixed model equations corresponding to the fixed effects in the dense part of the model formula, the second is a vector containing the E-BLUPs of the random effects and the third is a vector of E-solutions corresponding to the effects in the `sparse` formula. The names of the coefficients are the same as those in the respective formulae in the call to `asreml()` with factor levels appended and separated by "\_".
`vcoeff` | a list with three components, `fixed`, `random` and `sparse`, containing the unscaled variances of the coefficients. The actual variances are calculated as `vcoeff*object\$sigma2`.
`predictions` | a list object with components `pvals, sed, vcov` and `avsed`.
`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 link scale.
`residuals` | a vector containing the residuals from the model.
`hat` | the diagonal elements of the matrix W C^{-1} W^T, the so-called 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.
`nedf` | the residual degrees of freedom, `length(y)-rank(X)`.
`ai` | the inverse average information matrix of the variance parameters. A vector of length nk(nk+1)/2 where nk`= length(gammas)`holding the lower triangle row-wise.
`Cfixed` | reflexive generalised inverse of the coefficient matrix of the mixed model equations relating to the dense fixed effects (if `Cfixed=TRUE`, see `asreml.control()`). The returned object is a vector containing the lower triangle row-wise of C-inverse.
`Csparse` | non-zero elements of the reflexive generalised inverse matrix of the coefficient matrix for the sparse stored model terms nominated in the `Csparse` formula (see `asreml.control()`). The returned object is a data frame giving the row, column and non-zero element.
`family` | family object, the result of a call to `asreml.family`.
`call` | an image of the call that produced the object.
`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 G, 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 R, the error structure, including σ^2. This object may be used as the value of the R.param argument to provide initial parameter estimates to asreml for the error component of the model.

### See Also

`asreml` `asreml.control`