"IdtE" contains the results of model estimation. "IdtSngDE" extends "IdtE" assuming that the data can be carcherizes by a unique distribution (for instances, not considering partitions into different groups).
ModelNames: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:Indicates the model; currently, Gaussian or Skew-Normal distributions are implemented
ModelConfig:Configuration of the variance-covariance matrix: Case 1 through Case 4
NIVar:Number of interval variables
SelCrit:The model selection criterion; currently, AIC and BIC are implemented
logLiks:The logarithms of the likelihood function for the different cases
AICs:Value of the AIC criterion
BICs:Value of the BIC criterion
BestModel:Bestmodel indicates the best model according to the chosen selection criterion
SngD:Boolean flag indicating whether a single or a mixture of distribution were estimated
signature(Idt = "IdtE"): Selects the best model according to the chosen selection criterion (currently, AIC or BIC)
signature(object = "IdtE"): show S4 method for the IDtE-class
signature(Idt = "IdtE"): Performs statistical likelihood-ratio tests that evaluate the goodness-of-fit of a nested model against a more general one.
Brito, P., Duarte Silva, A. P. (2012), Modelling Interval Data with Normal and Skew-Normal Distributions. Journal of Applied Statistics 39(1), 3--20.
mle, fasttle, fulltle, MANOVA, RobMxtDEst,