SigEf_ps

SigEf_alphas

SigEf_betas

SigEf_gammas

print.summaryIData

==.IData

!=.IData

[.IData

[&lt;-.IData

show,IData-method

nrow,IData-method

ncol,IData-method

CovCase-methods

CovCase

MCDcnp2

C1CPgrad

C1CovPar

C2CPgrad

C2CovPar

C2GetCov

C2GetCovStderr

C2RestCovInd

C3CPgrad

C3CovPar

C3RestCovInd

C4CPgrad

C4CovPar

C4RestCovInd

C5CPgrad

C5RestCovInd

Cnf2MaxLik

CovC1toRestCov

CovtoParC2

EvalClrule

FreePar

GC2LogLikC.grad

GC2mLogLik

GC2mLogLik.grad

GetCovPar

Getvarofsmplmeansbygrp

ILogLikDNC

ILogLikNC

ILogLikNC1

IdtFDMxtSNmle

IdtHetMxtNmle

IdtNmle

IdtSNmle

MINPHIARG

MxtDist.fit

NestedBy

NextModel

ConfNestedBy

ConfNextModel

getConfig

ObsLik.Omegagrad

ObsLik.alphagrad

ObsLik.ksigrad

ObsLogLiks

NmleVCov

ObsLogLiks,IdtSngNDE-method

OmgInv.grad

OmgtoOmgbar.grad

PartoMatC2

RestCov

RestCov.grad

RestCovInd

RestCovj

Rfasttle

Rfulltle

RunfooforallComb

SKC1GetStderr

SKGetStderr

SKnpar

SNCMaxLik

SNCnf1MaxLik

Sigmagrad

SigmagradCnt

SigmasrgradCnt

Subsmplmle

Theta.ll.grad

VCovGC2LogLikC.grad

c2cind

c2rfind

cfsbmu0

cnvCPtoDP

cnvDPtoCP

dvec0ind

dvecind

error

fasttle1

fL.grad

fmdind

getfskpar

initparconf2

lftD

internal

MAINT.Data-internal

Implements methodologies for modelling interval data by Normal
and Skew-Normal distributions, considering appropriate parameterizations of
the variance-covariance matrix that takes into account the intrinsic nature of
interval data, and lead to four different possible configuration structures.
The Skew-Normal parameters can be estimated by maximum likelihood, while Normal
parameters may be estimated by maximum likelihood or robust trimmed maximum
likelihood methods.

Antonio Duarte Silva

MAINT.Data

Model and Analyse Interval Data

MAINT.Data-internal function

Operators, functions and other Internal MAINT.Data objects. — MAINT.Data-internal

Operators, functions and other Internal MAINT.Data objects.

MAINT.Data-internal: Operators, functions and other Internal MAINT.Data objects.

Description

Arguments