• Medientyp: E-Artikel
  • Titel: Best monotone M‐estimators
  • Beteiligte: Kolkiewicz, Adam W.
  • Erschienen: Wiley, 2003
  • Erschienen in: Canadian Journal of Statistics
  • Sprache: Englisch
  • DOI: 10.2307/3316090
  • ISSN: 0319-5724; 1708-945X
  • Schlagwörter: Statistics, Probability and Uncertainty ; Statistics and Probability
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  • Anmerkungen:
  • Beschreibung: <jats:title>Abstract</jats:title><jats:p>The author shows how to find M‐estimators of location whose generating function is monotone and which are optimal or close to optimal. It is easy to identify a consistent sequence of estimators in this class. In addition, it contains simple and efficient approximations in cases where the likelihood function is difficult to obtain. In some neighbourhoods of the normal distribution, the loss of efficiency due to the approximation is quite small. Optimal monotone M‐estimators can also be determined in cases when the underlying distribution is known only up to a certain neighbourhood. The author considers the e‐contamination model and an extension thereof that allows the distributions to be arbitrary outside compact intervals. His results also have implications for distributions with monotone score functions. The author illustrates his methodology using Student and stable distributions.</jats:p>