Journal article
A fast robust method for fitting gamma distributions
Statistical Papers, Vol.53(4), pp.1001-1014
2012
Abstract
The art of fitting gamma distributions robustly is described. In particular we compare methods of fitting via minimizing a Cramér Von Mises distance, an L 2 minimum distance estimator, and fitting a B-optimal M-estimator. After a brief prelude on robust estimation explaining the merits in terms of weak continuity and Fréchet differentiability of all the aforesaid estimators from an asymptotic point of view, a comparison is drawn with classical estimation and fitting. In summary, we give a practical example where minimizing a Cramér Von Mises distance is both efficacious in terms of efficiency and robustness as well as being easily implemented. Here gamma distributions arise naturally for “in control” representation indicators from measurements of spectra when using fourier transform infrared (FTIR) spectroscopy. However, estimating the in-control parameters for these distributions is often difficult, due to the occasional occurrence of outliers.
Details
- Title
- A fast robust method for fitting gamma distributions
- Authors/Creators
- B.R. Clarke (Author/Creator) - Murdoch UniversityP.L. McKinnon (Author/Creator) - Curtin UniversityG. Riley (Author/Creator) - Alcoa (United States)
- Publication Details
- Statistical Papers, Vol.53(4), pp.1001-1014
- Publisher
- Springer
- Identifiers
- 991005542301807891
- Copyright
- 2011 Springer-Verlag
- Murdoch Affiliation
- School of Chemical and Mathematical Science
- Language
- English
- Resource Type
- Journal article
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- 9.92 Statistical Methods
- 9.92.220 Robust Estimation
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- Statistics & Probability
- ESI research areas
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