Supplies a list of values including tolerances for singularity and
convergence assessment, for use functions involving EM within *MCLUST*.

`emControl(eps, tol, itmax, equalPro)`

## 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
log-likelihood and for parameter convergence in the inner loop for models
with iterative M-step ("VEI", "VEE", "EVE", "VVE", "VEV"), respectively.
The default is `c(1.e-5, sqrt(.Machine$double.eps))`

.
If only one number is supplied, it is used as the tolerance
for the outer iterations and the tolerance for the inner
iterations is as in the default.

- 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", "EVE", "VVE", "VEV"),
respectively. The default is
`c(.Machine$integer.max, .Machine$integer.max)`

allowing termination to be completely governed by `tol`

.
If only one number is supplied, it is used as the iteration
limit for the outer iteration only.

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

.

## Value

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

## Details

`emControl`

is provided for assigning values and defaults
for EM within *MCLUST*.

## Examples

```
irisBIC <- mclustBIC(iris[,-5], control = emControl(tol = 1.e-6))
summary(irisBIC, iris[,-5])
#> Best BIC values:
#> VEV,2 VEV,3 VVV,2
#> BIC -561.7285 -562.5508708 -574.01783
#> BIC diff 0.0000 -0.8224087 -12.28937
#>
#> Classification table for model (VEV,2):
#>
#> 1 2
#> 50 100
```