Q. What is the relation of the $stock component returned in the
result of ltsreg() to the quan observations whose residuals were
minimized?
A. The short answer is that the two are not the same. $stock is a list
of the observations used to create the fit. The quan observations used
in minimizing the objective are the ones associated with the smallest
sized residuals ($objective == (sum(sort(($residuals)^2)[1:quan]))/quan)
Q. Is there any way to guide ltsreg() to weight some observations as
more likely to be outliers?
A. There is an open implementation of ltsreg and of S-estimation in Marazzi's
ROBETH library which one can potentially modify.
Q. Any other references?
A.
P. J. Rousseeuw and A. M. Leroy (1987) Robust Regres-
sion and Outlier Detection. Wiley.
A. Marazzi (1993) Algorithms, Routines and S Functions
for Robust Statistics. Wadsworth & Brooks/Cole.
P. Rousseeuw and M. Hubert (1997) Recent developments
in PROGRESS. In L1-Statistical Procedures and Related
Topics ed Y. Dodge, IMS Lecture Notes volume 31, pp.
201-214.
I am also looking forward to replacements for lmsreg/ltsreg/cov.mve
under development for Venables & Ripley 3rd edition.
With appreciations to the list,
Arman Maghbouleh.
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