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

Description Usage Arguments Value See Also Examples

Description

Show description of a Rmixmod class to standard output.

Usage

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## S4 method for signature 'Model'
show(object)

## S4 method for signature 'MultinomialParameter'
show(object)

## S4 method for signature 'GaussianParameter'
show(object)

## S4 method for signature 'CompositeParameter'
show(object)

## S4 method for signature 'MixmodResults'
show(object)

## S4 method for signature 'Mixmod'
show(object)

## S4 method for signature 'Strategy'
show(object)

## S4 method for signature 'MixmodCluster'
show(object)

## S4 method for signature 'MixmodDAResults'
show(object)

## S4 method for signature 'MixmodLearn'
show(object)

## S4 method for signature '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

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  ## 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)

Rmixmod documentation built on June 26, 2018, 5:02 p.m.