A description of interval-valued variable outliers found by the MAINT.Data function getIdtOutl.
outliers:A vector of indices of the interval data units flaged as outliers.
MD2:A vector of squared robust Mahalanobis distances for all interval data units.
Nominal size of the null hypothesis that a given observation is not an outlier.
The assumed reference distributions used to find cutoffs defining the observations assumed as outliers. Alternatives are “ChiSq” and “CerioliBetaF” respectivelly for the usual Chi-squared, and the Beta and F distributions proposed by Cerioli (2010).
Whether a multicomparison correction of the nominal size (eta) for the outliers tests was performed. Alternatives are: ‘never’ -- ignoring the multicomparisons and testing all entities at the ‘eta’ nominal level. ‘always’ -- testing all n entitites at 1.- (1.-‘eta’^(1/n)).
Number of original observations in the original data set.
Number of total numerical variables (MidPoints and/or LogRanges) that may be responsible for the outliers.
Size of the subsets over which the trimmed likelihood was maximized when computing the robust Mahalanobis distances.
A logical vector indicanting which of the data units belong to the final trimmed subsetused to compute the tle estimates.
signature(object = "IdtOutl"): show S4 method for the IdtOutl-class.
signature(x = "IdtOutl"): plot S4 methods for the IdtOutl-class.
signature(x = "IdtOutl"): retrieves the vector of squared robust Mahalanobis distances for all data units.
signature(x = "IdtOutl"): retrieves the nominal size of the null hypothesis used to flag observations as outliers.
signature(x = "IdtOutl"): retrieves the assumed reference distributions used to find cutoffs defining the observations assumed as outliers.
signature(x = "IdtOutl"): retrieves the multicomparison correction used when flaging observations as outliers.
Pedro Duarte Silva <psilva@porto.ucp.pt>
Paula Brito <mpbrito.fep.up.pt>
Cerioli, A. (2010), Multivariate Outlier Detection with High-Breakdown Estimators.
Journal of the American Statistical Association 105 (489), 147--156.
Duarte Silva, A.P., Filzmoser, P. and Brito, P. (2017), Outlier detection in interval data. Advances in Data Analysis and Classification, 1--38.
getIdtOutl, fasttle, fulltle