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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).