IdtMxNDRE-class: Class IdtMxNDE

Description

IdtMxNDRE contains the results of a mixture Normal model robust parameter estimation, with the four different possible variance-covariance configurations.

Arguments

Slots

Hmcdt:: Indicates whether we consider an homocedastic (TRUE) or a hetereocedasic model (FALSE)
RobNmuE:: Matrix with the robust mean vectors estimates by group (each row refers to a group)
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 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 IdtMxNDRE class
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 IdtMxNDRE
Ngrps:: Inherited from class '>IdtMxE. Number of mixture components
rawSet: A vector with the trimmed subset elements used to compute the raw (not reweighted) MCD covariance estimate for the chosen configuration.
RewghtdSet: A vector with the final trimmed subset elements used to compute the fasttle estimates.
RobMD2: A vector with the robust squared Mahalanobis distances used to select the trimmed subset.
cnp2: A vector of length two containing the consistency correction factor and the finite sample correction factor of the final estimate of the covariance matrix.
raw.cov: A matrix with the raw MCD estimator used to compute the robust squared Mahalanobis distances of RobMD2.
raw.cnp2: A vector of length two containing the consistency correction factor and the finite sample correction factor of the raw estimate of the covariance matrix.
PerfSt: A a list with the following components: RepSteps: A list with one component by Covariance Configuration, containing a vector with the number of refinement steps performed by the fasttle algorithm by replication. RepLogLik: A list with one component by Covariance Configuration, containing a vector with the best log-likelihood found be fasttle algorithm by replication. StpLogLik: A list with one component by Covariance Configuration, containing a matrix with the evolution of the log-likelihoods found be fasttle algorithm by replication and refinement step.

Extends

Class '>IdtMxE, directly. Class '>IdtE, by class '>IdtMxE, distance 2.

Methods

No methods defined with class IdtMxNDRE in the signature.

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.

Duarte Silva, A.P., Filzmoser, P. and Brito, P. (2017), Outlier detection in interval data. Advances in Data Analysis and Classification, 1--38.