asreml.object {asreml} | R Documentation

## ASReml object

### Description

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 W C^{-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.

[Package asreml version 4.1.0.176 Index]