R: This (S3) class object contains a fitted linear mixed model...

asreml.object {asreml} | R Documentation

## This (S3) class object contains a fitted linear mixed model from the `asreml()` function

### Description

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 log-likelihood at completion of the `asreml` call.

- `vparameters`: The vector of variance components estimates from the model 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.

- `vparameters.type`: A numeric vector identifying the variance parameter types.

- `vparameters.pc`: Percentage change in `gammas` parameters over 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 E-BLUEs of 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` is returned.

- `Cfixed`: Reflexive generalized 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` is returned).

- `Csparse`: If `asreml.options()$Csparse` is not `NULL`, the non-zero elements of the reflexive generalized 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 elements.

- `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(attr(object$mf))` for details.

- `wrkv`: The residual working variables (if requested and available).

[Package asreml version 4.2.0.480 Index]