Ulogical-class

Define class unions for optional slots, e.g., for definition of slots which will be computed on demand.

classes

Outliers virtually exist in any datasets of any application field.
To avoid the impact of outliers, we need to use robust estimators.
Classical estimators of multivariate mean and covariance matrix are
the sample mean and the sample covariance matrix. Outliers will
affect the sample mean and the sample covariance matrix, and thus
they will affect the classical factor analysis which depends on
the classical estimators (Pison, G., Rousseeuw, P.J., Filzmoser,
P. and Croux, C. (2003) <doi:10.1016/S0047-259X(02)00007-6>).
So it is necessary to use the robust estimators of the sample
mean and the sample covariance matrix. There are several robust
estimators in the literature: Minimum Covariance Determinant estimator,
Orthogonalized Gnanadesikan-Kettenring, Minimum Volume Ellipsoid,
M, S, and Stahel-Donoho.
The most direct way to make multivariate analysis more robust is to replace
the sample mean and the sample covariance matrix of the classical estimators
to robust estimators (Maronna, R.A., Martin, D. and Yohai, V. (2006)
<doi:10.1002/0470010940>) (Todorov, V. and Filzmoser, P. (2009)
<doi:10.18637/jss.v032.i03>), which is our choice of robust factor
analysis. We created an object oriented solution for robust factor
analysis based on new S4 classes.

Frederic Bertrand

robustfa

Object Oriented Solution for Robust Factor Analysis

Ying-Ying Zhang (Robert)

Ulogical-class function

A virtual Class: No objects may be created from it.

Objects from the Class

No methods defined with class "Ulogical" in the signature.

Methods

Ying-Ying Zhang (Robert) <a href="/link/robertzhangyying%40qq.com?package=robustfa&version=1.1-0" data-mini-rdoc="robustfa::robertzhangyying@qq.com">robertzhangyying@qq.com</a>

Author

Class "Ulogical" — Ulogical-class

Ying-Ying Zhang (Robert) <a href='mailto:robertzhangyying@qq.com'>robertzhangyying@qq.com</a>

Ulogical-class: Class `"Ulogical"`

Description

Arguments

Objects from the Class

Methods

Author

References