Inference for mixtures of symmetric distributions

@inproceedings{Hunter2004InferenceFM,
  title={Inference for mixtures of symmetric distributions},
  author={D. R. Hunter and Shaoli Wang and Thomas P. Hettmansperger},
  year={2004}
}
This article discusses the problem of estimation of parameters in finite mixtures when the mixture components are assumed to be symmetric and to come from the same location family. We refer to these mixtures as semi-parametric because no additional assumptions other than symmetry are made regarding the parametric form of the component distributions. Because the class of symmetric distributions is so broad, identifiability of parameters is a major issue in these mixtures. We develop a notion of… CONTINUE READING
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