Journal article
Trimmed likelihood estimators for lifetime experiments and their influence functions
Statistics, Vol.50(3), pp.505-524
2016
Abstract
We study the behaviour of trimmed likelihood estimators (TLEs) for lifetime models with exponential or lognormal distributions possessing a linear or nonlinear link function. In particular, we investigate the difference between two possible definitions for the TLE, one called original trimmed likelihood estimator (OTLE) and one called modified trimmed likelihood estimator (MTLE) which is the finite sample version of a form for location and linear regression used by Bednarski and Clarke [Trimmed likelihood estimation of location and scale of the normal distribution. Aust J Statist. 1993;35:141–153, Asymptotics for an adaptive trimmed likelihood location estimator. Statistics. 2002;36:1–8] and Bednarski et al. [Adaptive trimmed likelihood estimation in regression. Discuss Math Probab Stat. 2010;30:203–219]. The OTLE is always an MTLE but the MTLE may not be unique even in cases where the OLTE is unique. We compare especially the functional forms of both types of estimators, characterize the difference with the implicit function theorem and indicate situations where they coincide and where they do not coincide. Since the functional form of the MTLE has a simpler form, we use it then for deriving the influence function, again with the help of the implicit function theorem. The derivation of the influence function for the functional form of the OTLE is similar but more complicated.
Details
- Title
- Trimmed likelihood estimators for lifetime experiments and their influence functions
- Authors/Creators
- C.H. Müller (Author/Creator)S. Szugat (Author/Creator)N. Celik (Author/Creator)B.R. Clarke (Author/Creator)
- Publication Details
- Statistics, Vol.50(3), pp.505-524
- Publisher
- Taylor & Francis
- Identifiers
- 991005542533307891
- Copyright
- © 2015 Taylor & Francis
- Murdoch Affiliation
- School of Engineering and Information Technology
- Language
- English
- Resource Type
- Journal article
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