ImpS {GSE}

Imputed S-estimator

Description

Computes the simple three-step estimator as described in the rejoinder of Agostinelli et al. (2015).

Usage

ImpS(x, alpha=0.95, method=c("bisquare","rocke"), init=c("emve","emve_c"), ...)

Arguments

x

a matrix or data frame.

alpha

quantile of the reference distribution in the univariate filter step (see gy.filt). Default is 0.95.

method

which loss function to use: 'bisquare', 'rocke'.

init

type of initial estimator. Currently this can either be "emve" (EMVE with uniform sampling, see Danilov et al., 2012) or "emve_c" (EMVE_C with cluster sampling, see Leung and Zamar, 2016). Default is "emve".

...

optional, additional arguments to be passed to GSE.

Details

This function computes the simple three-step estimator as described in the rejoinder in Agostinelli et al. (2015). The procedure has three steps:

In Step I, the method flags and removes cell-wise outliers using the Gervini-Yohai univariate only filter (see gy.filt).

In Step II, the method imputes the filtered cells using coordinate-wise medians.

In Step III, the method applies MVE-S to the filtered and imputed data from Step II (see GSE).

Value

The following gives the major slots in the output S4 object:

mu	Estimated location. Can be accessed via getLocation.
S	Estimated scatter matrix. Can be accessed via getScatter.
xf	Filtered data matrix from the first step of 2SGS. Can be accessed via getFiltDat.

Author(s)

Andy Leung [e-mail], Claudio Agostinelli, Ruben H. Zamar, Victor J. Yohai

References

Agostinelli, C., Leung, A. , Yohai, V.J., and Zamar, R.H. (2015) Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination. TEST.

See Also

GSE, gy.filt