IdtSNgenda-class {MAINT.Data} | R Documentation |
Class "IdtSNgenda"
Description
IdtSNgenda contains the results of discriminant analysis for the interval data, based on a general Skew-Normal model.
Slots
prior
: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.
ksi
:Matrix with the direct location parameter ("ksi") estimates for each group.
eta
:Matrix with the direct scaled sekwness parameter ("eta") estimates for each group.
scaling
:For each group g, scaling[,,g] is a matrix which transforms interval-valued observations so that in each group the scale-association matrix ("Omega") is spherical.
mu
:Matrix with the centred location parameter ("mu") estimates for each group.
gamma1
:Matrix with the centred sekwness parameter ("gamma1") estimates for each group.
ldet
:Vector of half log determinants of the dispersion matrix.
lev
:Levels of the grouping factor.
CovCase
:Configuration case of the variance-covariance matrix: Case 1 through Case 4
Methods
- predict
signature(object = "IdtSNgenda")
: Classifies interval-valued observations in conjunction with snda.- show
signature(object = "IdtSNgenda")
: show S4 method for the IdtSNgenda-class- CovCase
signature(object = "IdtSNgenda")
: Returns the configuration case of the variance-covariance matrix
Author(s)
Pedro Duarte Silva <psilva@porto.ucp.pt>
Paula Brito <mpbrito.fep.up.pt>
References
Azzalini, A. and Dalla Valle, A. (1996), The multivariate skew-normal distribution. Biometrika 83(4), 715–726.
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.