IdtMxSNDE contains the results of a mixture model estimation for the Skew-Normal model, with the four different possible variance-covariance configurations.
Hmcdt
:Indicates whether we consider an homocedastic location model (TRUE) or a general model (FALSE)
CovConfCases
:List of the considered configurations
grouping
:Inherited from class "IdtMxE"
. 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 case 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"
. 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 "IdtMxSNDE"
Ngrps
:Inherited from class "IdtMxE"
. Number of mixture components
No methods defined with class "IdtMxSNDE" in the signature.
Brito, P., Duarte Silva, A. P. (2012), Modelling Interval Data with Normal and Skew-Normal Distributions. Journal of Applied Statistics 39(1), 3--20.