Rmixmod (version 2.1.5)

show: Show description of a Rmixmod class to standard output.

Description

Show description of a Rmixmod class to standard output.

Usage

# S4 method for Model
show(object)
# S4 method for MultinomialParameter
show(object)
# S4 method for GaussianParameter
show(object)
# S4 method for CompositeParameter
show(object)
# S4 method for MixmodResults
show(object)
# S4 method for Mixmod
show(object)
# S4 method for Strategy
show(object)
# S4 method for MixmodCluster
show(object)
# S4 method for MixmodDAResults
show(object)
# S4 method for MixmodLearn
show(object)
# S4 method for MixmodPredict
show(object)

Arguments

object

a Rmixmod object: a '>Strategy, a '>Model, a '>GaussianParameter, a '>MultinomialParameter, a '>MixmodResults, a '>MixmodCluster, a '>MixmodLearn or a '>MixmodPredict.

Value

NULL. Prints to standard out.

See Also

show

Examples

# NOT RUN {
  ## for strategy
  strategy <- mixmodStrategy()
  show(strategy)

  ## for Gaussian models
  gmodel <- mixmodGaussianModel()
  show(gmodel)
  ## for multinomial models
  mmodel <- mixmodMultinomialModel()
  show(mmodel)

  ## for clustering
  data(geyser)
  xem <- mixmodCluster(geyser,3)
  show(xem)
  ## for Gaussian parameters
  show(xem["bestResult"]["parameters"])

  ## for discriminant analysis
  # start by extract 10 observations from iris data set
  iris.partition<-sample(1:nrow(iris),10)
  # then run a mixmodLearn() analysis without those 10 observations
  learn<-mixmodLearn(iris[-iris.partition,1:4], iris$Species[-iris.partition])
  # create a MixmodPredict to predict those 10 observations
  prediction <- mixmodPredict(data=iris[iris.partition,1:4], classificationRule=learn["bestResult"])
  # show results
  show(prediction)

# }