mclustOptions {mclust} | R Documentation

## 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 machine precision `.Machine\$double.eps`, which is approximately $2e-16$ on IEEE-compliant machines.
`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-5)`.
`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)` allowing termination to be completely governed by `tol`.
`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 volume and shape "VEI": diagonal, varying volume, equal shape "EVI": diagonal, equal volume, varying shape "VVI": diagonal, varying volume and shape "EEE": ellipsoidal, equal volume, shape, and orientation "EEV": ellipsoidal, equal volume and equal shape "VEV": ellipsoidal, equal shape "VVV": ellipsoidal, varying volume, shape, and orientation
`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","VVV")`, giving the unconstrained model in each case.
`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(17,0,10,4,11,18,6,7,3,16,2,12,8,15,1,9,14,13,5)`.

### 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.

### 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.

### 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

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