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 ε(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.
Bignozzi, V., Macci, C., Petrella, L. (2020). Large deviations for method-of-quantiles estimators of one-dimensional parameters. COMMUNICATIONS IN STATISTICS. THEORY AND METHODS, 49(5), 1132-1157 [10.1080/03610926.2018.1554134].
Large deviations for method-of-quantiles estimators of one-dimensional parameters
Bignozzi, Valeria;
2020
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 ε(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.
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