Idtqda contains the results of Quadratic Discriminant Analysis for the interval data
Prior probabilities of class membership; if unspecified, the class proportions for the training set are used; if present, the probabilities should be specified in the order of the factor levels.
Matrix with the mean vectors for each group
A three-dimensional array. For each group, g, scaling[,,g] is a matrix which transforms interval-valued observations so that within-groups covariance matrix is spherical.
Vector of half log determinants of the dispersion matrix.
Levels of the grouping factor
Configuration case of the variance-covariance matrix: Case 1 through Case 4
signature(object = "Idtqda"): Classifies interval-valued observations in conjunction with qda.
signature(object = "Idtqda"): show S4 method for the Idtqda-class
signature(object = "Idtqda"): Returns the configuration case of the variance-covariance matrix
Pedro Duarte Silva <email@example.com>
Paula Brito <mpbrito.fep.up.pt>
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. and Brito, P. (2015), Discriminant analysis of interval data: An assessment of parametric and distance-based approaches. Journal of Classification 39(3), 516–541.