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Journal Articles Biometrika Year : 2010

Accurate and Robust Tests for Indirect Inference

Abstract

In this paper we propose accurate parameter and over-identification tests for indirect inference. Under the null hypothesis the new tests are asymptotically χ2-distributed with a relative error of order n−1. They exhibit better finite sample accuracy than classical tests for indirect inference, which have the same asymptotic distribution but an absolute error of order n−1/2. Robust versions of the tests are also provided. We illustrate their accuracy in nonlinear regression, Poisson regression with overdispersion and diffusion models.

Dates and versions

hal-00585938 , version 1 (14-04-2011)

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Cite

Veronika Czellar, Elvezio Ronchetti. Accurate and Robust Tests for Indirect Inference. Biometrika, 2010, 97 (3), pp.621-630. ⟨10.1093/biomet/asq040⟩. ⟨hal-00585938⟩

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