fsdalts.object: Description of 'fsdalts' Objects

In fsdaR: Robust Data Analysis Through Monitoring and Dynamic Visualization

Description of fsdalts Objects

Description

An object of class fsdalts.object holds information about the result of a call to fsreg.

Value

The object itself is basically a list with the following components:

rew	If rew=TRUE all subsequent output refers to reweighted else no reweighting is done.
beta	p-by-1 vector containing the estimated regression parameters.
bs	p x 1 vector containing the units forming subset associated with bLMS (bLTS).
residuals	residuals.
scale	scale estimate of the residuals.
weights	Vector like y containing weights. The elements of this vector are 0 or 1. These weights identify the h observations which are used to compute the final LTS (LMS) estimate. sum(weights)=h if there is not a perfect fit otherwise sum(weights) can be greater than h
h	The number of observations that have determined the LTS (LMS) estimator, i.e. the value of h.
outliers	vector containing the list of the units declared as outliers using confidence level specified in input scalar conflev.
conflev	confidence level which is used to declare outliers. Remark: conflev will be used to draw the horizontal lines (confidence bands) in the plots. Default value is 0.975
singsub	Number of subsets wihtout full rank. Notice that if this number is greater than 0.1*(number of subsamples) a warning is produced
X	the data matrix X
y	the response vector y

The object has class "fsdalts".

Examples

## Not run:   
    data(hbk, package="robustbase")
    (out <- fsreg(Y~., data=hbk, method="LTS"))
    class(out)
    summary(out)

## End(Not run)

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