ClustMMDD (version 1.0.3)

EmOptions: Display the current Expectation and Maximization options.

Description

Display the Expectation and Maximization algorithm current options.

Usage

EmOptions()

Value

• A list of EM options :
  • epsi :
  {The upper bound of the relative increasing on log-likelihood.}
• nberSmallEM :
  The number of random parameter points from which to run small EMs. The estimated parameter point associated to the higher maximum log-likelihood is then used to initialise the final EM run.
• nberIterations :
  The number of iterations in each small EM.
• typeSmallEM :
  0 = classic EM, 1 = SEM and 2 = CEM.
• typeEM :
  0 = classic EM, 1 = SEM and 2 = CEM.
• nberMaxIterations :
  The maximum number of iterations in the final EM if the convergence is slow.
• putThreshold :
  The indication of whether all parameter estimates are positive.

References

• http://projecteuclid.org/euclid.ejs/1379596773{Dominique Bontemps and Wilson Toussile (2013)} : Clustering and variable selection for categorical multivariate data. Electronic Journal of Statistics, Volume 7, 2344-2371, ISSN.
• http://link.springer.com/article/10.1007%2Fs11634-009-0043-x{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.

See Also

setEmOptions for setting EM options.

Examples

EmOptions()
setEmOptions(list(epsi = 1e-6))
EmOptions()
setEmOptions()	# To set default values
EmOptions()