Robust fitting of mixtures using the trimmed likelihood estimator

@article{Neykov2007RobustFO,
  title={Robust fitting of mixtures using the trimmed likelihood estimator},
  author={N. M. Neykov and Peter Filzmoser and R. Dimova and P. N. Neytchev},
  journal={Computational Statistics & Data Analysis},
  year={2007},
  volume={52},
  pages={299-308}
}
The maximum likelihood estimator (MLE) has commonly been used to estimate the unknown parameters in a finite mixture of distributions. However, the MLE can be very sensitive to outliers in the data. In order to overcome this the trimmed likelihood estimator (TLE) is proposed to estimate mixtures in a robust way. The superiority of this approach in comparison with the MLE is illustrated by examples and simulation studies. Moreover, as a prominent measure of robustness, the breakdown point (BDP… CONTINUE READING

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