'>MultinomialModel] class using new/initialize.Initialization method. Used internally in the `Rmixmod' package.
Initialization method. Used internally in the `Rmixmod' package.
Initialization method. Used internally in the `Rmixmod' package.
Initialization method. Used internally in the `Rmixmod' package.
Initialization method. Used internally in the `Rmixmod' package.
Initialization method. Used internally in the `Rmixmod' package.
Initialization method. Used internally in the `Rmixmod' package.
Initialization method. Used internally in the `Rmixmod' package.
# S4 method for MultinomialModel
initialize(.Object, listModels, free.proportions,
equal.proportions, variable.independency, component.independency)# S4 method for GaussianModel
initialize(.Object, listModels, family,
free.proportions, equal.proportions)
# S4 method for CompositeModel
initialize(.Object, listModels, free.proportions,
equal.proportions, variable.independency, component.independency)
# S4 method for Mixmod
initialize(.Object, data, dataType, models, weight,
knownLabels, xmlIn, xmlOut, seed, trace, massiccc)
# S4 method for Strategy
initialize(.Object, algo, nbTry, initMethod, nbTryInInit,
nbIterationInInit, nbIterationInAlgo, epsilonInInit, epsilonInAlgo, seed,
parameter, labels)
# S4 method for MixmodCluster
initialize(.Object, data = NULL, nbCluster = NULL,
dataType = NULL, models = NULL, strategy = NULL, criterion = NULL,
weight = NULL, knownLabels = NULL, seed = -1, xmlIn = NULL,
xmlOut = NULL, trace = 0, massiccc = 0)
# S4 method for MixmodLearn
initialize(.Object, data = NULL, knownLabels = NULL,
dataType = NULL, models = NULL, criterion = "CV", nbCVBlocks = 10,
weight = NULL, seed = -1, xmlIn = NULL, xmlOut = NULL, trace = 0,
massiccc = 0)
# S4 method for MixmodPredict
initialize(.Object, data, classificationRule,
xmlIn = NULL, xmlOut = NULL, trace = 0, massiccc = 0)