Benchmark testing of algorithms for very robust regression: FS, LMS and LTS
The methods of very robust regression resist up to 50% of outliers. The algorithms for very robust regression rely on selecting numerous subsamples of the data. We describe new algorithms for LMS and LTS estimators that have increased efficiency due to improved combinatorial sampling. These and other publicly available algorithms are compared for outlier detection. An algorithm using the forward search has the best properties for both size and power of the outlier tests.
TORTI Francesca;
PERROTTA Domenico;
ATKINSON Anthony C.;
RIANI Marco;
2012-04-20
ELSEVIER SCIENCE BV
JRC67506
0167-9473,
http://www.sciencedirect.com/science/article/pii/S0167947312000680,
https://publications.jrc.ec.europa.eu/repository/handle/JRC67506,
10.1016/j.csda.2012.02.003,
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