Large deviations for method-of-quantiles estimators of one-dimensional parameters
Valeria Bignozzi,
Claudio Macci and
Lea Petrella
Communications in Statistics - Theory and Methods, 2020, vol. 49, issue 5, 1132-1157
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.
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:49:y:2020:i:5:p:1132-1157
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DOI: 10.1080/03610926.2018.1554134
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