IdtMANOVA-class: Class "IdtMANOVA"

Description

IdtMANOVA extends"" directly, containing the results of MANOVA tests on the interval-valued data. This class is not used directly, but is the basis for different specializations according to the model assumed for the distribution in each group. In paticular, the following specializations of IdtMANOVA are currently implemented:

"IdtClMANOVA" extends IdtMANOVA, assuming a classical (i.e., homocedastic gaussian) setup.

"IdtHetNMANOVA" extends IdtMANOVA, assuming a heterocedastic gaussian set-up.

"IdtLocNMANOVA" extends IdtMANOVA, assuming a Skew-Normal location model set-up.

"IdtLocNSNMANOVA" extends IdtMANOVA, assuming either a homocedastic gaussian or Skew-Normal location model set-up.

"IdtGenNMANOVA" extends IdtMANOVA, assuming a Skew-Normal general model set-up.

"IdtLocNSNMANOVA" extends IdtMANOVA, assuming either a heterocedastic gaussian or Skew-Normal general model set-up.

Arguments

Slots

NIVar:: Number of interval variables.
grouping:: Factor indicating the group to which each observation belongs to.
H0res:: Model estimates under the null hypothesis.
H1res:: Model estimates under the alternative hypothesis.
QuiSq:: Inherited from class "LRTest". Value of the Qui-Square statistics corresponding to the performed test.
df:: Inherited from class "LRTest". Degrees of freedom of the Qui-Square statistics.
pvalue:: Inherited from class "LRTest". p-value of the Qui-Square statistics value, obtained from the Qui-Square distribution with df degrees of freedom.
H0logLik:: Inherited from class "LRTest". Logarithm of the Likelihood function under the null hypothesis.
H1logLik:: Inherited from class "LRTest". Logarithm of the Likelihood function under the alternative hypothesis.

Methods

show: signature(object = "IdtMANOVA"): show S4 method for the IdtMANOVA-classes.
H0res: signature(object = "IdtMANOVA"): retrieves the model estimates under the null hypothesis.
H1res: signature(object = "IdtMANOVA"): retrieves the model estimates under the alternative hypothesis.
lda: signature(x = "IdtClMANOVA"): Linear Discriminant Analysis using the estimated model parameters.
lda: signature(x = "IdtLocNSNMANOVA"): Linear Discriminant Analysis using the estimated model parameters.
qda: signature(x = "IdtHetNMANOVA"): Quadratic Discriminant Analysis using the estimated model parameters.
qda: signature(x = "IdtGenNSNMANOVA"): Quadratic Discriminant Analysis using the estimated model parameters.
snda: signature(x = "IdtLocSNMANOVA"): Discriminant Analysis using maximum likelihood parameter estimates of SkewNormal mixtures assuming a "location" model (i.e., groups differ only in location parameters).
snda: signature(x = "IdtLocNSNMANOVA"): Discriminant Analysis using maximum likelihood parameter estimates of SkewNormal mixtures assuming a "location" model (i.e., groups differ only in location parameters).
snda: signature(x = "IdtGenSNMANOVA"): Discriminant Analysis using maximum likelihood parameter estimates of SkewNormal mixtures assuming a general model (i.e., groups differ in all parameters).
snda: signature(x = "IdtGenNSNMANOVA"): Discriminant Analysis using maximum likelihood parameter estimates of SkewNormal mixtures assuming a general model (i.e., groups differ in all parameters).

Extends

Class "", directly.

References

Brito, P., Duarte Silva, A. P. (2012): "Modelling Interval Data with Normal and Skew-Normal Distributions". Journal of Applied Statistics, Volume 39, Issue 1, 3-20.