corfwdplot {fsdaR} | R Documentation |
Monitoring the correlations between consecutive distances or residuals
Description
Provides a method for obtaining the maximum empirical efficiency
(in case of MM estimates) or maximum empirical breakdownplot (in case of S estimates) or
maximum subset size (in case of forward search),
using various measures of correlation between the n
Mahalanobis distances or residuals at
adjacent values of efficiecy, breakdown point or subset size.
Usage
corfwdplot(out, trace = FALSE, ...)
Arguments
out |
An object of S3 class returned by one of the estimation functions with the
monitoring option selected ( The needed elements of
|
trace |
Whether to print intermediate results. Default is |
... |
potential further arguments passed to lower level functions. |
Value
A ggplot
plot object which can be printed on screen or to a file.
Author(s)
FSDA team, valentin.todorov@chello.at
Examples
## Not run:
data(hbk, package="robustbase")
(out <- fsmult(hbk[,1:3], monitoring=TRUE))
corfwdplot(out)
(out1 <- smult(hbk, monitoring=TRUE, trace=TRUE))
corfwdplot(out1)
(out2 <- mmmult(hbk[,1:3], monitoring=TRUE, trace=TRUE))
corfwdplot(out2)
(out3 <- fsreg(hbk[,1:3], hbk[,4], monitoring=TRUE, trace=TRUE, method="FS"))
corfwdplot(out3)
(out4 <- fsreg(hbk[,1:3], hbk[,4], monitoring=TRUE, trace=TRUE, method="S"))
corfwdplot(out4)
(out5 <- fsreg(hbk[,1:3], hbk[,4], monitoring=TRUE, trace=TRUE, method="MM"))
corfwdplot(out5)
## End(Not run)