| IdtSngNDE-class {MAINT.Data} | R Documentation |
Class IdtSngNDE
Description
Contains the results of a single class maximum likelihood estimation for the Normal distribution, with the four different possible variance-covariance configurations.
Slots
mleNmuE:Vector with the maximum likelihood mean vectors estimates
mleNmuEse:Vector with the maximum likelihood means' standard errors
CovConfCases:List of the considered configurations
ModelNames:Inherited from class
IdtE. The model acronym formed by a "N", indicating a Normal model, followed by the configuration (Case 1 through Case 4)ModelType:Inherited from class
IdtE. Indicates the model; always set to "Normal" in objects of the IdtSngNDE classModelConfig:Inherited from class
IdtE. Configuration of the variance-covariance matrix: Case 1 through Case 4NIVar:Inherited from class
IdtE. Number of interval variablesSelCrit:Inherited from class
IdtE. The model selection criterion; currently, AIC and BIC are implementedlogLiks:Inherited from class
IdtE. The logarithms of the likelihood function for the different casesAICs:Inherited from class
IdtE. Value of the AIC criterionBICs:Inherited from class
IdtE. Value of the BIC criterionBestModel:Inherited from class
IdtE. Bestmodel indicates the best model according to the chosen selection criterionSngD:Inherited from class
IdtE. Boolean flag indicating whether a single or a mixture of distribution were estimated. Always set to TRUE in objects of class IdtSngNDE
Extends
Class IdtSngDE, directly.
Class IdtE, by class IdtSngDE, distance 2.
Methods
No methods defined with class IdtSngNDE in the signature.
Author(s)
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.
See Also
IData, mle, IdtSngNDRE, IdtSngSNDE, IdtMxNDE