Contains the results of a single class robust estimation for the Normal distribution, with the four different possible variance-covariance configurations.
RobNmuE:Matrix with the maximum likelihood mean vectors estimates
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 IdtSngNDRE class
ModelConfig:Inherited from class '>IdtE. Configuration of the variance-covariance matrix: Case 1 through Case 4
NIVar: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:BICs: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 TRUE in objects of class IdtSngNDRE
rawSetA vector with the trimmed subset elements used to compute the raw (not reweighted) MCD covariance estimate for the chosen configuration.
RewghtdSetA vector with the final trimmed subset elements used to compute the tle estimates.
RobMD2A vector with the robust squared Mahalanobis distances used to select the trimmed subset.
cnp2A vector of length two containing the consistency correction factor and the finite sample correction factor of the final estimate of the covariance matrix.
raw.covA matrix with the raw MCD estimator used to compute the robust squared Mahalanobis distances of RobMD2.
raw.cnp2A vector of length two containing the consistency correction factor and the finite sample correction factor of the raw estimate of the covariance matrix.
PerfStA 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.
No methods defined with class IdtSngNDRE 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.
Duarte Silva, A.P., Filzmoser, P. and Brito, P. (2017), Outlier detection in interval data. Advances in Data Analysis and Classification, 1--38.