fsdaR (version 0.9-0)

sregeda.object: Description of sregeda Objects

Description

An object of class sregeda.object holds information about the result of a call to fsreg when method="S" and monitoring=TRUE.

Value

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

Beta

matrix containing the S estimator of regression coefficients for each value of bdp.

Scale

vector containing the estimate of the scale (sigma) for each value of bdp. This is the value of the objective function.

BS

p x 1 vector containing the units forming best subset associated with S estimate of regression coefficient.

RES

n x length(bdp) matrix containing the monitoring of scaled residuals for each value of bdp.

Weights

n x length(bdp) matrix containing the estimates of the weights for each value of bdp

Outliers

Boolean matrix containing the list of the units declared as outliers for each value of bdp using confidence level specified in input scalar conflev.

conflev

Confidence level which is used to declare units as outliers. Remark: conflev will be used to draw the horizontal line (confidence band) in the plot.

Singsub

Number of subsets wihtout full rank. Notice that singsub[bdp[jj]] > 0.1*(number of subsamples) produces a warning

rhofunc

Specifies the rho function which has been used to weight the residuals.

rhofuncparam

Vector which contains the additional parameters for the specified rho function which has been used. For hyperbolic rho function the value of k =sup CVC. For Hampel rho function the parameters a, b and c.

X

the data matrix X

y

the response vector y

The object has class "sregeda".

Examples

if (FALSE) {
    data(hbk, package="robustbase")
    (out <- fsreg(Y~., data=hbk, method="S", monitoring=TRUE))
    class(out)
    summary(out)
}