IData-class: Class IData

In MAINT.Data: Model and Analyse Interval Data

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

NbMicroUnits:

An integer vector with the number of micro data units by interval-valued observation (or an empty vector, if not applicable)

Methods

show

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

nrow

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

ncol

signature(x = "IData"): returns the number of of Interval-valued variables.

dim

signature(x = "IData"): returns a vector with the of number statistical units as first element, and the number of Interval-valued variables as second element.

rownames

signature(x = "IData"): returns the row (entity) names for an object of class IData.

colnames

signature(x = "IData"): returns column (variable) names for an object of class IData.

names

signature(x = "IData"): returns column (variable) names for an object of class IData.

MidPoints

signature(Sdt = "IData"): returns a data frame with MidPoints for an object of class IData.

LogRanges

signature(Sdt = "IData"): returns a data frame with LogRanges for an object of class IData.

Ranges

signature(Sdt = "IData"): returns an data frame with Ranges for an object of class IData.

NbMicroUnits

signature(Sdt = "IData"): returns an integer vector with the number of micro data units by interval-valued observation for an object of class IData.

head

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

tail

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

plot

signature(x = "IData"): plot S4 methods 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.

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.

Author(s)

Pedro Duarte Silva <[e-mail]>
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., Filzmoser, P. and Brito, P. (2017), Outlier detection in interval data. Advances in Data Analysis and Classification, 1–38.

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

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