- 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