MAINT.Data (version 1.0.1)

IData-class: Class "IData"

Description

A data-array of interval-valued data is an array where each of the NObs rows, corresponding to each entity under analysis, contains the observed intervals of the NIVar descriptive variables.

Slots

MidP:

A data-frame of the midpoints of the observed intervals

LogR:

A data-frame of the logarithms of the ranges of the observed intervals

ObsNames:

An optional vector of names assigned to the individual observations.

VarNames:

An optional vector of names to be assigned to the Interval-Valued Variables.

NObs:

Number of entities under analysis (cases)

NIVar:

Number of interval variables

Methods

head

signature(x = "IData"): head S4 method for the IData-class.

show

signature(object = "IData"): show S4 method for the IData-class.

nrow

signature(x = "IData"): returns the number of entities (observations).

ncol

signature(x = "IData"): returns the number of Iterval Variables.

show

signature(object = "IData"): show S4 method for the IData-class.

tail

signature(x = "IData"): tail S4 method for the IData-class.

mle

signature(x = "IData"): Maximum likelihood estimation.

fasttle

signature(x = "IData"): Fast trimmed maximum likelihood estimation.

fulltle

signature(x = "IData"): Exact trimmed maximum likelihood estimation.

mle

signature(x = "IData"): Maximum likelihood estimation.

RobMxtDEst

signature(x = "IData"): Robust estimation of distribution mixtures for interval-valued data.

MANOVA

signature(x = "IData"): MANOVA tests on the interval-valued data.

lda

signature(x = "IData"): Linear Discriminant Analysis using maximum likelihood parameter estimates of Gaussian mixtures.

qda

signature(x = "IData"): Quadratic Discriminant Analysis using maximum likelihood parameter estimates of Gaussian mixtures.

Roblda

signature(x = "IData"): Linear Discriminant Analysis using robust estimates of location and scatter.

Robqda

signature(x = "IData"): Quadratic Discriminant Analysis using robust estimates of location and scatter.

snda

signature(x = "IData"): Discriminant Analysis using maximum likelihood parameter estimates of SkewNormal mixtures.

References

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

Hadi, A. S. and Luceno, A. (1997), Maximum trimmed likelihood estimators: a unified approach, examples, and algorithms. Computational Statistics and Data Analysis 25(3), 251--272.

Noirhomme-Fraiture, M., Brito, P. (2011), Far Beyond the Classical Data Models: Symbolic Data Analysis. Statistical Analysis and Data Mining 4(2), 157--170.

See Also

IData, mle, fasttle, fulltle, RobMxtDEst, MANOVA, lda, qda, Roblda, Robqda