Journal article
Robust estimation of k-component univariate normal mixtures
Annals of the Institute of Statistical Mathematics, Vol.46(1), pp.83-93
1994
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.
Details
- Title
- Robust estimation of k-component univariate normal mixtures
- Authors/Creators
- B.R. Clarke (Author/Creator) - Murdoch UniversityC.R. Heathcote (Author/Creator) - Australian National University
- Publication Details
- Annals of the Institute of Statistical Mathematics, Vol.46(1), pp.83-93
- Identifiers
- 991005540958907891
- Copyright
- © 1994 The Institute of Statistical Mathematics.
- Murdoch Affiliation
- School of Chemical and Mathematical Science
- Language
- English
- Resource Type
- Journal article
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- Citation topics
- 9 Mathematics
- 9.92 Statistical Methods
- 9.92.220 Robust Estimation
- Web Of Science research areas
- Statistics & Probability
- ESI research areas
- Mathematics