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STICERD Econometrics Seminar Series

Least Trimmed Square: Nuisance Parameter Free Asymptotics

Vanessa Berenguer-Rico (University of Oxford)

Thursday 21 March 2024 14:00 - 15:30

Many of our seminars and public events this year will continue as in person or as hybrid (online and in person) events. Please check our website listings and Twitter feed @STICERD_LSE for updates.

Unless otherwise specified, in-person seminars are open to the public.

Those unable to join the seminars in-person are welcome to participate via zoom if the event is hybrid.

About this event

The Least Trimmed Squares (LTS) regression estimator is known to be very robust to the presence of ‘outliers’. It is based on a clear and intuitive idea: in a sample of size n, it searches for the h-subsample of observations with the smallest sum of squared residuals. The remaining n−h observations are declared ‘outliers’. Fast algorithms for its computation exist. Nevertheless, the existing asymptotic theory for LTS, based on the traditional -contamination model, shows that the asymptotic behaviour of both regression and scale estimators depend on nuisance parameters. Using a recently proposed new model, in which the LTS estimator is maximum likelihood, we show that the asymptotic behaviour of both the LTS regression and scale estimators are free of nuisance parameters. Thus, with the new model as a benchmark, standard inference procedures apply while allowing a broad range of contamination.

STICERD Econometrics seminars are held on Thursdays in term time at 14.00-15.30, in SAL 3.05, unless specified otherwise.

Seminar organisers: Professor Tai Otsu and Dr. Vassilis Hajivassiliou.

For further information please contact Sadia Ali:

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