IdtMxE-class: Class IdtMxE

Description

IdtMxE extends the IdtE class, assuming that the data can be characterized by a mixture of distributions, for instances considering partitions of entities into different groups.

Arguments

Slots

grouping:: Factor indicating the group to which each observation belongs to
ModelNames:: Inherited from class IdtE. The model acronym, indicating the model type (currently, N for Normal and SN for Skew-Normal), and the configuration (Case 1 through Case 4)
ModelType:: Inherited from class IdtE. Indicates the model; currently, Gaussian or Skew-Normal distributions are implemented.
ModelConfig:: Inherited from class IdtE. Configuration of the variance-covariance matrix: Case 1 through Case 4
NIVar:: Inherited from class IdtE. Number of interval variables
SelCrit:: Inherited from class IdtE. The model selection criterion; currently, AIC and BIC are implemented
logLiks:: Inherited from class IdtE. The logarithms of the likelihood function for the different cases
AICs:: Inherited from class IdtE. Value of the AIC criterion
BICs:: Inherited from class IdtE. Value of the BIC criterion
BestModel:: Inherited from class IdtE. Bestmodel indicates the best model according to the chosen selection criterion
SngD:: Inherited from class IdtE. Boolean flag indicating whether a single or a mixture of distribution were estimated. Always set to FALSE in objects of class "IdtMxE"
Ngrps:: Number of mixture components

Extends

Class IdtE, directly.

Methods

No methods defined with class "IdtMxE" in the signature.

Author

Pedro Duarte Silva <psilva@porto.ucp.pt>
Paula Brito <mpbrito.fep.up.pt>

References

Brito, P., Duarte Silva, A. P. (2012), Modelling Interval Data with Normal and Skew-Normal Distributions. Journal of Applied Statistics 39(1), 3--20.