FaCov: Robust Factor Analysis

In robustfa: Object Oriented Solution for Robust Factor Analysis

Robust Factor Analysis

Description

Robust factor analysis are obtained by replacing the classical covariance matrix by a robust covariance estimator. This can be one of the available estimators in rrcov, i.e., MCD, OGK, M, S, SDE, or MVE estimator.

Usage

FaCov(x, ...)
## S3 method for class 'formula'
FaCov(formula, data = NULL, factors = 2, cor = FALSE, method = "mle", 
scoresMethod = "none", ...)
## Default S3 method:
FaCov(x, factors = 2, cor = FALSE, cov.control = rrcov::CovControlMcd(), 
method = c("mle", "pca", "pfa"), 
scoresMethod = c("none", "regression", "Bartlett"), ...)

Arguments

x	A formula or a numeric matrix or an object that can be coerced to a numeric matrix.
...	Arguments passed to or from other methods.
formula	A formula with no response variable, referring only to numeric variables.
data	An optional data frame (or similar: see model.frame) containing the variables in the formula.
factors	The number of factors to be fitted.
cor	A logical value indicating whether the calculation should use the covariance matrix (cor = FALSE) or the correlation matrix (cor = TRUE).
method	The method of factor analysis, one of "mle" (the default), "pca", and "pfa".
scoresMethod	Type of scores to produce, if any. The default is "none", "regression" gives Thompson's scores, "Bartlett" gives Bartlett's weighted least-squares scores.
cov.control	Specifies which covariance estimator to use by providing a CovControl-class object. The default is CovControlMcd-class which will indirectly call CovMcd. If cov.control=NULL is specified, the classical estimates will be used by calling CovClassic.

Details

FaCov, serving as a constructor for objects of class FaCov-class is a generic function with "formula" and "default" methods.

Value

An S4 object of class FaCov-class which is a subclass of the virtual class Fa-class.

Author(s)

Ying-Ying Zhang (Robert) [e-mail]

References

Zhang, Y. Y. (2013), An Object Oriented Solution for Robust Factor Analysis.

See Also

FaClassic-class, FaCov-class, FaRobust-class, Fa-class

Examples

data("hbk")
hbk.x = hbk[,1:3] 

##
## faCovPcaRegMcd is obtained from FaCov.default
##
faCovPcaRegMcd = FaCov(x = hbk.x, factors = 2, method = "pca",
scoresMethod = "regression", cov.control = rrcov::CovControlMcd()); faCovPcaRegMcd

##
## In fact, it is equivalent to use FaCov.formula
## faCovForPcaRegMcd = faCovPcaRegMcd
##
faCovForPcaRegMcd = FaCov(~., data = as.data.frame(hbk.x), 
factors = 2, method = "pca", scoresMethod = "regression", 
cov.control = rrcov::CovControlMcd()); faCovForPcaRegMcd

robustfa documentation built on April 16, 2023, 5:18 p.m.