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The Semiparametric Normal Variance‐Mean Mixture Model

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  • Lars Korsholm

Abstract

We study the normal variance‐mean mixture model from a semiparametric point of view, i.e. we let the mixing distribution belong to a non‐parametric family. The main results are consistency of the non‐parametric maximum likelihood estimator and construction of an asymptotically normal and efficient estimator for the Euclidian part of the parameter. We study the model according to the theory outlined in the monograph by Bickel et al. (1993) and apply a general result (based on the theory of empirical processes) for semiparametric models from van der Vaart (1996) to prove asymptotic normality and efficiency of the proposed estimator.

Suggested Citation

  • Lars Korsholm, 2000. "The Semiparametric Normal Variance‐Mean Mixture Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(2), pages 227-261, June.
    • Handle: RePEc:bla:scjsta:v:27:y:2000:i:2:p:227-261
    DOI: 10.1111/1467-9469.00187
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