Small sample corrections for US and MCD
Faculty of Sciences. Mathematics and Computer Science
Faculty of Social Sciences. Communication Sciences
Heidelberg :Physica, 2003
International Conference on Robust Statistics (ICOR 2001), July 23-27, 2001, Vorau, Austria
University of Antwerp
The least trimmed squares estimator and the minimum covariance determinant estimator Rousseeuw (1984) are frequently used robust estimators of regression and of location and scatter. Consistency factors can be computed for both methods to make the estimators consistent at the normal model. However, for small data sets these factors do not make the estimator unbiased. Based on simulation studies we therefore construct formulas which allow us to compute small sample correction factors for all sample sizes and dimensions without having to carry out any new simulations. We give some examples to illustrate the effect of the correction factor.