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Create a table of downweighted observations based on a rrfit object within a cgOneFactorFit object. A cgOneFactorDownweightedTable class object is created.
# S4 method for cgOneFactorFit
downweightedTable(fit, cutoffwt, display="print", ...)
An object of class cgOneFactorDownweightedTable
, with the
following slots:
contents
A data frame where each row is an observation from the fitted data set that meets the cutoff criteria, and these columns:
group
The group identified from the fitted data.
endpoint
The observed response value.
weight
The weight associated to the observation from the resistant / robust fit.
pct down-weighted
An expression of the weight in terms of percent reduction from the maximum of 1.
If no observations meet the cutoff criteria,
the contents
slot is set to NULL
.
cutoffwt
Taken from the specified cutoffwt
argument
value.
settings
A list of settings carried from the
cgOneFactorFit
object, and the addition
of the specified cutoffwt
argument in the method call above. These are used
for the print.cgOneFactorDownweightedTable
method,
invoked for example when
display="print"
.
A fit object of class cgOneFactorFit
.
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 observations that were downweighted by at least 10%.
One of three valid values:
"print"
The default value; It calls a print
method for the
created cgOneFactorDownweightedTable
object, which is
a formatted text output of the table(s).
"none"
Supresses any printing. Useful, for example, when just assignment of the resulting object is desired.
"show"
Calls the default showDefault
method, which
will just print out the cgOneFactorDownweightedTable
components.
Additional arguments. None are currently defined for this method.
Bill Pikounis [aut, cre, cph], John Oleynick [aut], Eva Ye [ctb]
If no observations meet the cutoff criteria, a text message of the
cgOneFactorDownweightedTable
content emptiness is output
instead.
The reported weights are in the scale of the observation, not the
sum of squared errors representation for the likelihood. Thus they are
derived from the square root of the $w
component from
a MASS::rlm
fit object.
Venables, W. N. and Ripley, B. D. (2002), Modern Applied Statistics with S. Fourth edition. Springer.
cgOneFactorFit
, MASS::rlm
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%
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