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Large deviations for method-of-quantiles estimators of one-dimensional parameters

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  • Valeria Bignozzi
  • Claudio Macci
  • Lea Petrella

Abstract

We consider method-of-quantiles estimators of unknown one-dimensional parameters, namely the analogue of method-of-moments estimators obtained by matching empirical and theoretical quantiles at some probability level λ∈(0,1). The aim is to present large deviation results for these estimators as the sample size tends to infinity. We study in detail several examples; for specific models we discuss the choice of the optimal value of λ and we compare the convergence of the method-of-quantiles and method-of-moments estimators.

Suggested Citation

  • Valeria Bignozzi & Claudio Macci & Lea Petrella, 2020. "Large deviations for method-of-quantiles estimators of one-dimensional parameters," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(5), pages 1132-1157, March.
    • Handle: RePEc:taf:lstaxx:v:49:y:2020:i:5:p:1132-1157
    DOI: 10.1080/03610926.2018.1554134
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