emControl {mclust} | R Documentation |
Supplies a list of values including tolerances for singularity and convergence assessment, for use functions inivoling EM within MCLUST.
emControl(eps, tol, itmax, equalPro)
eps |
A scalar tolerance associated with deciding when to terminate
computations due to computational singularity in
covariances. Smaller values of |
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 |
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 |
equalPro |
Logical variable indicating whether or not the mixing proportions are
equal in the model. Default: |
emControl
is provided for assigning values and defaults
for EM within MCLUST.
A named list in which the names are the names of the arguments and the values are the values supplied to the arguments.
C. Fraley and A. E. Raftery (2002). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611-631.
C. Fraley and A. E. Raftery (2006). MCLUST Version 3 for R: Normal Mixture Modeling and Model-Based Clustering, Technical Report no. 504, Department of Statistics, University of Washington.
em
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estep
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me
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mstep
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mclustBIC
irisBIC<- mclustBIC(iris[,-5], control = emControl(tol = 1.e-6)) summary(irisBIC, iris[,-5])