mixAK interface
# S4 method for lcMethodMixAK_GLMM
getName(object)# S4 method for lcMethodMixAK_GLMM
getShortName(object)
# S4 method for lcMethodMixAK_GLMM
responseVariable(object)
# S4 method for lcMethodMixAK_GLMM
preFit(method, data, envir, verbose, ...)
# S4 method for lcMethodMixAK_GLMM
fit(method, data, envir, verbose, ...)
# S4 method for lcModelMixAK_GLMM
postprob(object, ...)
# S4 method for lcModelMixAK_GLMM
predictForCluster(object, newdata, cluster, what = "mu", ...)
# S4 method for lcModelMixAK_GLMM
predictForCluster(object, newdata, cluster, what = "mu", ...)
# S3 method for lcModelMixAK_GLMM
coef(object, ..., stat = "Mean")
# S3 method for lcModelMixAK_GLMM
deviance(object, ...)
# S4 method for lcModelMixAK_GLMMlist
postprob(object, ...)
# S4 method for lcModelMixAK_GLMMlist
predictForCluster(object, newdata, cluster, what = "mu", ...)
The object to extract the label from.
The lcMethod object.
The data, as a data.frame, on which the model will be trained.
The environment in which the lcMethod should be evaluated
A R.utils::Verbose object indicating the level of verbosity.
Additional arguments.
Optional data.frame for which to compute the model predictions. If omitted, the model training data is used.
Cluster trajectory predictions are made when ids are not specified.
The cluster name (as character) to predict for.
The distributional parameter to predict. By default, the mean response 'mu' is predicted. The cluster membership predictions can be obtained by specifying what = 'mb'.
The aggregate statistic to extract. The mean is used by default.