Journal article
Small sample bias correction for Huber's Proposal-2 scale M-estimator
Australian & New Zealand Journal of Statistics, Vol.46(4), pp.649-656
2004
Abstract
The most popular and perhaps universal estimator of location and scale in robust estimation, where the population is normal with possible small departures, is Huber's Proposal-2 M-estimator. This paper gives the first-order small sample bias correction for the scale estimator, verifying the calculation through theory and simulation. Other ways of reducing small sample bias, say by jackknifing or bootstrapping, can be computationally intensive, and would not be routinely used with this iteratively derived estimator. It is suggested that bias-reduced estimates of scale are most useful when forming confidence intervals for location and/or scale based on the asymptotic distribution.
Details
- Title
- Small sample bias correction for Huber's Proposal-2 scale M-estimator
- Authors/Creators
- B.R. Clarke (Author/Creator)C.J. Milne (Author/Creator)
- Publication Details
- Australian & New Zealand Journal of Statistics, Vol.46(4), pp.649-656
- Publisher
- Blackwell Publishing Inc.
- Identifiers
- 991005544971507891
- Copyright
- 2004 Australian Statistical Publishing Association Inc.
- 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