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On a Problem of Statistical Inference in Null Recurrent Diffusions
Authors:R Höpfner  Yu Kutoyants
Institution:(1) Johannes Gutenberg Universität Mainz, D-55099 Mainz, Germany;(2) Laboratoire Statistique et Processus, Université du Maine, F-72085 Le Mans Cedex 09, France
Abstract:We consider a particular example of statistical inference in null recurrent one-dimensional diffusions. In a first parametric model, we prove local asymptotic mixed normality (LAMN) and efficiency of the sequence of maximum likelihood estimates (MLE): its speed of convergence is n agr/2 with agr ranging over (0, 1). In a second semiparametric model (where in addition an unknown nuisance function with known compact support is included in the drift), we prove a local asymptotic minimax bound and specify asymptotically efficient estimates for the unknown parameter.
Keywords:diffusions  null recurrence  limit theorems  parametric inference  semiparametric model  LAMN  convolution theorem  local asymptotic minimax bound
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