`priorControl.Rd`

Specify a conjugate prior for Gaussian mixtures.

`priorControl(functionName = "defaultPrior", ...)`

- functionName
The name of the function specifying the conjugate prior. By default the function

`defaultPrior`

is used, and this can also be used as a template for alternative specification.- ...
Optional named arguments to the function specified in

`functionName`

together with their values.

A list with the function name as the first component. The remaining components (if any) consist of a list of arguments to the function with assigned values.

The function `priorControl`

is used to specify a conjugate prior
for EM within *MCLUST*.

Note that, as described in `defaultPrior`

, in the multivariate
case only 10 out of 14 models may be used in conjunction with a prior, i.e.
those available in *MCLUST* up to version 4.4.

C. Fraley and A. E. Raftery (2007).
Bayesian regularization for normal mixture estimation and model-based
clustering. *Journal of Classification 24:155-181*.

```
# default prior
irisBIC <- mclustBIC(iris[,-5], prior = priorControl())
#> Warning: The presence of BIC values equal to NA is likely due to one or more of the mixture proportions being estimated as zero, so that the model estimated reduces to one with a smaller number of components.
summary(irisBIC, iris[,-5])
#> Best BIC values:
#> VEV,2 VEV,3 VVV,2
#> BIC -580.8136 -587.403843 -592.51283
#> BIC diff 0.0000 -6.590289 -11.69928
#>
#> Classification table for model (VEV,2):
#>
#> 1 2
#> 50 100
# no prior on the mean; default prior on variance
irisBIC <- mclustBIC(iris[,-5], prior = priorControl(shrinkage = 0))
#> Warning: The presence of BIC values equal to NA is likely due to one or more of the mixture proportions being estimated as zero, so that the model estimated reduces to one with a smaller number of components.
summary(irisBIC, iris[,-5])
#> Best BIC values:
#> VEV,2 VEV,3 VVV,2
#> BIC -580.2861 -586.792195 -592.07132
#> BIC diff 0.0000 -6.506112 -11.78523
#>
#> Classification table for model (VEV,2):
#>
#> 1 2
#> 50 100
```