MANOVA-methods: Methods for Function MANOVA in Package 'MAINT.Data'

In MAINT.Data: Model and Analyse Interval Data

Methods for Function MANOVA in Package ‘MAINT.Data’

Description

Function MANOVA performs MANOVA tests based on likelihood ratios allowing for both Gaussian and Skew-Normal distributions and homoscedastic or heteroscedastic setups. Methods H0res and H1res retrieve the model estimates under the null and alternative hypothesis, and method show displays the MANOVA results.

Usage

MANOVA(Sdt, grouping, Model=c("Normal","SKNormal","NrmandSKN"), CovCase=1:4, 
		SelCrit=c("BIC","AIC"), Mxt=c("Hom","Het","Loc","Gen"), 
                CVtol=1.0e-5, k2max=1e6,
		OptCntrl=list(), onerror=c("stop","warning","silentNull"), ...)

## S4 method for signature 'IdtMANOVA'
H0res(object)
## S4 method for signature 'IdtMANOVA'
H1res(object)
## S4 method for signature 'IdtMANOVA'
show(object)

Arguments

object	An object representing a MANOVA analysis on interval-valued units.
Sdt	An IData object representing interval-valued units.
grouping	Factor indicating the group to which each observation belongs to.
Model	The joint distribution assumed for the MidPoint and LogRanges. Current alternatives are “Normal” for Gaussian distributions, “SKNormal” for Skew-Normal and “NrmandSKN” for both Gaussian and Skew-Normal distributions.
CovCase	Configuration of the variance-covariance matrix: a set of integers between 1 and 4.
SelCrit	The model selection criterion.
Mxt	Indicates the type of mixing distributions to be considered. Current alternatives are “Hom” (homoscedastic) and “Het” (heteroscedastic) for Gaussian models, “Loc” (location model – groups differ only on their location parameters) and “Gen” “Loc” (general model – groups differ on all parameters) for Skew-Normal models.
CVtol	Tolerance level for absolute value of the coefficient of variation of non-constant variables. When a MidPoint or LogRange has an absolute value within-groups coefficient of variation below CVtol, it is considered to be a constant.
k2max	Maximal allowed l2-norm condition number for correlation matrices. Correlation matrices with condition number above k2max are considered to be numerically singular, leading to degenerate results.
OptCntrl	List of optional control parameters to be passed to the optimization routine. See the documentation of RepLOptim for a description of the available options.
onerror	Indicates whether an error in the optimization algorithm should stop the current call, generate a warning, or return silently a NULL object.
...	Other named arguments.

Value

An object of class IdtMANOVA, containing the estimation and test results.

See Also

IdtMANOVA, RepLOptim

Examples

#Create an Interval-Data object containing the intervals of temperatures by quarter 
# for 899 Chinese meteorological stations.
ChinaT <- IData(ChinaTemp[1:8])

#Classical (homoscedastic) MANOVA tests

ManvChina <- MANOVA(ChinaT,ChinaTemp$GeoReg)
cat("China, MANOVA by geografical regions results =\n")
print(ManvChina)

#Heteroscedastic MANOVA tests

HetManvChina <- MANOVA(ChinaT,ChinaTemp$GeoReg,Mxt="Het")
cat("China, heterocedastic MANOVA by geografical regions results =\n")
print(HetManvChina)

#Skew-Normal based MANOVA assuming the the groups differ only according to location parameters
## Not run: 

SKNLocManvChina <- MANOVA(ChinaT,ChinaTemp$GeoReg,Model="SKNormal",Mxt="Loc")
cat("China, Skew-Normal MANOVA (location model) by geografical regions results =\n")
print(SKNLocManvChina)

#Skew-Normal based MANOVA assuming the the groups may differ in all parameters

SKNGenManvChina <- MANOVA(ChinaT,ChinaTemp$GeoReg,Model="SKNormal",Mxt="Gen")
cat("China, Skew-Normal MANOVA (general model)  by geografical regions results =\n")
print(SKNGenManvChina)


## End(Not run)

MAINT.Data documentation built on April 4, 2023, 9:09 a.m.