# Robust estimation of k-component univariate normal mixtures

Clarke, B.R. and Heathcote, C.R.
(1994)
*Robust estimation of k-component univariate normal mixtures.*
Annals of the Institute of Statistical Mathematics, 46
(1).
pp. 83-93.

*Subscription may be required

*No subscription required

## Abstract

The estimating equations derived from minimising a L2 distance between the empirical distribution function and the parametric distribution representing a mixture of k normal distributions with possibly different means and/or different dispersion parameters are given explicitly. The equations are of the M estimator form in which the psi function is smooth, bounded and has bounded partial derivatives. As a consequence it is shown that there is a solution of the equations which is robust. In particular there exists a weakly continuous, Fréchet differentiable root and hence there is a consistent root of the equations which is asymptotically normal. These estimating equations offer a robust alternative to the maximum likelihood equations, which are known to yield nonrobust estimators.

Publication Type: | Journal Article |
---|---|

Murdoch Affiliation: | School of Chemical and Mathematical Science |

Copyright: | © 1994 The Institute of Statistical Mathematics. |

URI: | http://researchrepository.murdoch.edu.au/id/eprint/4792 |

Item Control Page |