read.or.compute: Read a given model from a file or compute the estimates of...
In ClustMMDD: Variable Selection in Clustering by Mixture Models for Discrete Data

Description Usage Arguments Details Author(s) References See Also

Read a given model from a file or compute the estimates of the parameters if not found. This function is not available for users.

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read.or.compute(xdata, xK, xS, xReferenceModel, xReferenceModelsIndex,
  xNberExploredModels, xFileNameExploredModels, cte = as.double(1),
  header = TRUE)

`xdata`	A list of dataset and several description paramaters such as frequencies.
`xK`	The number of components (clusters or populations).
`xS`	The subset of relevant variables.
`xReferenceModel`	The indicator of if the model is a reference model in an exclusion step of the backward-stepwise explorer.
`xReferenceModelsIndex`	The vector indicating the models that have once been a reference at an exclusion step.
`xNberExploredModels`	The current number of explored models.
`xFileNameExploredModels`	The explored models.
`cte`	A constant real.
`header`	Indication of the presence of header in the file.

Not available for users.

Wilson Toussile

Dominique Bontemps and Wilson Toussile (2013) : Clustering and variable selection for categorical multivariate data. Electronic Journal of Statistics, Volume 7, 2344-2371, ISSN.
Wilson Toussile and Elisabeth Gassiat (2009) : Variable selection in model-based clustering using multilocus genotype data. Adv Data Anal Classif, Vol 3, number 2, 109-134.

dimJump.R for data driven calibration of the penality function, and model.selection.R for model selection.

ClustMMDD documentation built on May 2, 2019, 2:44 p.m.