cg (version 1.0-2)

downweightedTable: Create a table of downweighted observations from a Resistant & Robust fit.

Description

Create a table of downweighted observations in a resistant & robust fit with the cg package.

Usage

downweightedTable(fit, cutoffwt, display="print", ...)

Arguments

fit

A fit object created with a fit method from the cg package.

cutoffwt

It has no default and must be specified as a numeric between 0 and 1 exclusive. It is a threshold. All observations that fall beneath the threshold will be identified. For example, a cutoffwt=0.90 will yield those

display

One of three valid values: [object Object],[object Object],[object Object]

...

Additional arguments, depending on the specific method written for the object. See the method-specific documentation for additional details.

Value

• A method-specific downweightedTable object is returned. See the specific methods for discussion of return values.

concept

• weights
• resistance
• robust

References

Venables, W. N. and Ripley, B. D. (2002), Modern Applied Statistics with S. Fourth edition. Springer.

See Also

downweightedTable.cgOneFactorFit, MASS::rlm

Examples

#### One Factor data

data(canine)
canine.data <- prepareCGOneFactorData(canine, format="groupcolumns",
                                      analysisname="Canine",
                                      endptname="Prostate Volume",
                                      endptunits=expression(plain(cm)^3),
                                      digits=1, logscale=TRUE, refgrp="CC")
canine.fit <- fit(canine.data)

canine.dwtable <- downweightedTable(canine.fit, cutoff=0.95)

downweightedTable(canine.fit, cutoff=0.75) ## No observation
                                           ## downweighted at least 25\%

## Paired Difference data

anorexiaFT.data <- prepareCGPairedDifferenceData(anorexiaFT, format="groupcolumns",
                                                 analysisname="Anorexia FT",
                                                 endptname="Weight",
                                                 endptunits="lbs",
                                                 expunitname="Patient",
                                                 digits=1,
                                                 logscale=TRUE)
anorexiaFT.fit <- fit(anorexiaFT.data)

downweightedTable(anorexiaFT.fit, cutoffwt=0.25) ## No observation

downweightedTable(anorexiaFT.fit, cutoffwt=0.75) ## downweighted at least 25\%