a character string naming a comma delimited file with a header line and three columns for the variance component name, initial value and constraint code, respectively.a list object derived from the random formula, holding initial parameter estimates and boundary constraints for each term, or.The default is id(units) if not explicitly specified. Variance models for the residual component of the model can be specified using special model functions.įor single-section univariate models, the residual variance model determines the computational mode: If the residual variance model specifies a correlation structure (includes id()), then the model is fitted on the gamma scale, otherwise the model is fitted on the sigma scale. The default is ∼ units, where the reserved word units is defined as seq(1,nrow(data)) and is automatically included in the model frame. Wald statistics are not available for sparse fixed terms in order to reduce the computing load.Ī formula object specifying the residual model any term specified on the left of the ∼ expression is ignored. This argument has the same general characteristics as fixed, but there can be no left side to the ∼ expression. Variance structures imposed on random terms are specified using special model functions.Ī formula object, specifying the fixed effects for which the full variance-covariance matrix is not required. This argument has the same general characteristics as fixed, but there can be no left side to the ∼ operator. If the response ( y) evaluates to a matrix then a factor trait with levels dimnames(y)] is added to the model frame, and must be explicitly included in the model formulae.Ī formula object specifying the random effects in the model.
If data is given, all names used in all formulae should appear in the data frame. A model with the intercept as the only fixed effect can be specified as ∼1 there must be at least one fixed effect specified. ) Arguments fixedĪ formula object specifying the fixed terms in the model, with the response on the left of a ∼ operator, and the terms, separated by + operators, on the right.
Prune = list(), combine = list(), uid = list(), mef = list(),
Knot.points = list(), pwr.points = list(), wald = list(), Vcm = vcm.lm(), vcc = matrix(NA), family = asr_gaussian(),Īsmv = NULL, mbf = list(), group = list(),Įquate.levels = character(0), start.values = FALSE, Na.action = na.method(), subset, weights, predict = predict.asreml(), G.param = list(), R.param = list(), data = sys.parent(), Usage asreml(fixed = y ~ 1, random = ~NULL, sparse = ~NULL, residual = ~NULL, Asreml estimates variance components under a general linear mixed model by residual maximum likelihood (REML).
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