Article ID Journal Published Year Pages File Type
1149407 Journal of Statistical Planning and Inference 2010 19 Pages PDF
Abstract

The present article considers estimating a parameter θθ in an imprecise probability model (P¯θ)θ∈Θ. This model consists of coherent upper previsions P¯θ which are given by finite numbers of constraints on expectations. A minimum distance estimator is defined in this case and its asymptotic properties are investigated. It is shown that the minimum distance can be approximately calculated by discretizing the sample space. Finally, the estimator is applied in a simulation study and on a real data set.

Related Topics
Physical Sciences and Engineering Mathematics Applied Mathematics
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