corfwdplot: Monitoring the correlations between consecutive distances or...

In fsdaR: Robust Data Analysis Through Monitoring and Dynamic Visualization

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 (monitoring=TRUE): fsreda.object, sregeda.object, mmregeda.object, fsmeda.object, smulteda.object or mmmulteda.object. This is a list containing the monitoring of minimum Mahalanobis distance in case of multivariate analysis or the monitoring of residuals in case of regression. The needed elements of out are MAL: matrix containing the squared Mahalanobis distances monitored in each step of the forward search. Every row is associated with a unit (row of data matrix Y). This matrix can be created using one of the functions fsmult, smult or mmmult with the monitoring option selected, i.e. monitoring=TRUE. RES: matrix containing the residuals monitored in each step of the forward search. Every row is associated with a unit (row of data matrix Y). This matrix can be created using the function fsreg with the monitoring option selected, i.e. monitoring=TRUE . bdp: a vector containing breakdown point values that have been used, in case of S estimates. eff: a vector containing efficiency values that have been used, in case of MM estimates.
trace	Whether to print intermediate results. Default is trace=FALSE.
...	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, [e-mail]

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)

fsdaR documentation built on March 31, 2023, 8:18 p.m.