R/PLNmixturefamily-class.R
PLNmixturefamily.RdThe function PLNmixture() produces an instance of this class.
This class comes with a set of methods, some of them being useful for the user:
See the documentation for getBestModel(), getModel() and plot().
The function PLNmixture, the class PLNmixturefit
PLNmodels::PLNfamily -> PLNmixturefamily
clustersvector indicating the number of clusters considered is the successively fitted models
Inherited methods
new()helper function for forward smoothing: split a group
Initialize all models in the collection.
PLNmixturefamily$new(
clusters,
responses,
covariates,
offsets,
formula,
control
)clustersthe dimensions of the successively fitted models
responsesthe matrix of responses common to every models
covariatesthe matrix of covariates common to every models
offsetsthe matrix of offsets common to every models
formulamodel formula used for fitting, extracted from the formula in the upper-level call
controla list for controlling the optimization. See details.
controla list for controlling the optimization. See details.
optimize()Call to the optimizer on all models of the collection
smooth()function to restart clustering to avoid local minima by smoothing the loglikelihood values as a function of the number of clusters
plot()Lineplot of selected criteria for all models in the collection
PLNmixturefamily$plot(criteria = c("loglik", "BIC", "ICL"), reverse = FALSE)criteriaA valid model selection criteria for the collection of models. Any of "loglik", "BIC" or "ICL" (all).
reverseA logical indicating whether to plot the value of the criteria in the "natural" direction (loglik - 0.5 penalty) or in the "reverse" direction (-2 loglik + penalty). Default to FALSE, i.e use the natural direction, on the same scale as the log-likelihood..
getBestModel()Extract best model in the collection
PLNmixturefamily$getBestModel(crit = c("BIC", "ICL", "loglik"))crita character for the criterion used to performed the selection. Either
"BIC", "ICL" or "loglik". Default is ICL
a PLNmixturefit object