The role of Hájek's convolution theorem in statistical theory
Rudolf Beran (1995)
Kybernetika
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Displaying similar documents to “Finite sample optimality of extremes and mid-range”
The role of Hájek's convolution theorem in statistical theory
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Annales scientifiques de l'Université de Clermont. Mathématiques
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Estimating quantiles with Linex loss function. Applications to VaR estimation
Ryszard Zieliński (2005)
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Sometimes, e.g. in the context of estimating VaR (Value at Risk), underestimating a quantile is less desirable than overestimating it, which suggests measuring the error of estimation by an asymmetric loss function. As a loss function when estimating a parameter θ by an estimator T we take the well known Linex function exp{α(T-θ)} - α(T-θ) - 1. To estimate the quantile of order q ∈ (0,1) of a normal distribution N(μ,σ), we construct an optimal estimator in the class of all estimators...
A new class of semi-parametric estimators of the second order parameter.
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Adaptive procedures
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