mclust (version 2.1-14)

mclustOptions: Set control values for use with MCLUST.

Description

Supplies a list of values including tolerances for singularity and convergence assessment, and an enumeration of models for use with MCLUST.

Usage

mclustOptions(eps, tol, itmax, equalPro, warnSingular, emModelNames,
              hcModelName, symbols)

Arguments

eps

A scalar tolerance associated with deciding when to terminate computations due to computational singularity in covariances. Smaller values of eps allow computations to proceed nearer to singularity. The default is the relative mac

tol

A vector of length two giving relative convergence tolerances for the loglikelihood and for parameter convergence in the inner loop for models with iterative M-step ("VEI", "VEE", "VVE", "VEV"), respectively. The default is c(1.e-5,1.e-

itmax

A vector of length two giving integer limits on the number of EM iterations and on the number of iterations in the inner loop for models with iterative M-step ("VEI", "VEE", "VVE", "VEV"), respectively. The default is c(Inf,Inf) a

equalPro

Logical variable indicating whether or not the mixing proportions are equal in the model. Default: equalPro = FALSE.

warnSingular

A logical value indicating whether or not a warning should be issued whenever a singularity is encountered. The default is warnSingular = TRUE.

emModelNames

A vector of character strings associated with multivariate models in MCLUST. The default includes strings encoding all of the multivariate models available: "EII": spherical, equal volume "VII": spherical, unequal volume "EEI": diagonal, equal

hcModelName

A vector of two character strings giving the name of the model to be used in the hierarchical clustering phase for univariate and multivariate data, respectively, in EMclust and EMclustN. The default is c("V","V

symbols

A vector whose entries are either integers corresponding to graphics symbols or single characters for plotting for classifications. Classes are assigned symbols in the given order. The default is c(17,0,10,4,11,18,6,7,3,16,2,12,8,15,

Value

• A named list in which the names are the names of the arguments and the values are the values supplied to the arguments.

References

C. Fraley and A. E. Raftery (2002a). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611-631. See http://www.stat.washington.edu/mclust. C. Fraley and A. E. Raftery (2002b). MCLUST:Software for model-based clustering, density estimation and discriminant analysis. Technical Report, Department of Statistics, University of Washington. See http://www.stat.washington.edu/mclust.

Details

mclustOptions is provided for assigning values to the .Mclust list, which is used to supply default values to various functions in MCLUST. Calls to mclustOptions do not in themselves affect the outcome of computations.

See Also

.Mclust

Examples

data(iris)
irisMatrix <- as.matrix(iris[,1:4])
irisClass <- iris[,5]

.Mclust
.Mclust <- mclustOptions(tol = 1.e-6, emModelNames = c("VII", "VVI", "VVV"))
.Mclust
irisBic <- EMclust(irisMatrix)
summary(irisBic, irisMatrix)
.Mclust <- mclustOptions() # restore default values
.Mclust