mixAK interface
# S4 method for lcMethodMixAK_GLMM
getArgumentDefaults(object)# S4 method for lcMethodMixAK_GLMM
getArgumentExclusions(object)
# 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 lcMethod or lcModel object.
An object inheriting from lcMethod with all its arguments having been evaluated and finalized.
A data.frame representing the transformed training data.
The environment containing variables generated by prepareData() and preFit().
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.