mixAK interface
# S4 method for lcMethodMixAK_GLMM
getArgumentDefaults(object)# S4 method for lcMethodMixAK_GLMM
getArgumentExclusions(object)
# S4 method for lcMethodMixAK_GLMM
getCitation(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 object.
Not used.
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.
A data.frame
of trajectory data for which to compute trajectory assignments.
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.
lcMethodMixAK_GLMM mixAK::GLMM_MCMC