mstepE {mclust} | R Documentation

## M-step in the EM algorithm for a parameterized MVN mixture model.

### Description

Maximization step in the EM algorithm for a parameterized MVN mixture model.

### Usage

    mstepE(data, z, equalPro, noise = FALSE, ...)
    mstepV(data, z, equalPro, noise = FALSE, ...)
    mstepEII(data, z, equalPro, noise = FALSE, ...)
    mstepVII(data, z, equalPro, noise = FALSE, ...)
    mstepEEI(data, z, equalPro, noise = FALSE, eps, warnSingular, ...)
    mstepVEI(data, z, equalPro, noise = FALSE, eps, tol, itmax, warnSingular, ...)
    mstepEVI(data, z, equalPro, noise = FALSE, eps, warnSingular, ...)
    mstepVVI(data, z, equalPro, noise = FALSE, eps, warnSingular, ...)
    mstepEEE(data, z, equalPro, noise = FALSE, ...)
    mstepEEV(data, z, equalPro, noise = FALSE, eps, warnSingular, ...)
    mstepVVV(data, z, equalPro, noise = FALSE, ...)

### Arguments

`data` | A numeric vector, matrix, or data frame of observations. Categorical variables are not allowed. If a matrix or data frame, rows correspond to observations and columns correspond to variables.
`z` | A matrix whose `[i,k]`th entry is the conditional probability of the ith observation belonging to the kth component of the mixture.
`equalPro` | A logical value indicating whether or not the components in the model are present in equal proportions. The default is `.Mclust\$equalPro`.
`noise` | A logical value indicating whether or not the model includes a Poisson noise component. The default assumes there is no noise component.
`eps` | A scalar tolerance for deciding when to terminate computations due to computational singularity in covariances. Smaller values of `eps` allows computations to proceed nearer to singularity. The default is `.Mclust\$eps`. Not used for models "EII", "VII", "EEE", "VVV".
`tol` | For models with iterative M-step ("VEI", "VEE", "VVE", "VEV"), a scalar tolerance for relative convergence of the parameters. The default is `.Mclust\$tol`.
`itmax` | For models with iterative M-step ("VEI", "VEE", "VVE", "VEV"), an integer limit on the number of EM iterations. The default is `.Mclust\$itmax`.
`warnSingular` | A logical value indicating whether or not a warning should be issued whenever a singularity is encountered. The default is `.Mclust\$warnSingular`. Not used for models "EII", "VII", "EEE", "VVV".
`...` | Provided to allow lists with elements other than the arguments can be passed in indirect or list calls with `do.call`.

### Value

A list including the following components:

`mu` | A matrix whose kth column is the mean of the kth component of the mixture model.
`sigma` | For multidimensional models, a three dimensional array in which the `[,,k]`th entry gives the the covariance for the kth group in the best model. <br> For one-dimensional models, either a scalar giving a common variance for the groups or a vector whose entries are the variances for each group in the best model.
`pro` | A vector whose kth component is the mixing proportion for the kth component of the mixture model.
`z` | A matrix whose `[i,k]`th entry is the conditional probability of the ith observation belonging to the kth component of the mixture.
`modelName` | A character string identifying the model (same as the input argument).
`Attributes:` | `"info"` Information on the iteration. `"warn"` An appropriate warning if problems are encountered in the computations.

### 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

`mstep`, `me`, `estep`, `mclustOptions`

### Examples

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

    mstepVII(data = irisMatrix, z = unmap(irisClass))

[Package mclust version 2.1-10 Index]