Local influence for functional comparative calibration models with replicated data

Patricia Giménez () and María Patat

Statistical Papers, 2014, vol. 55, issue 2, 454 pages

Abstract: We investigate local influence analysis in functional comparative calibration models with replicated data. A method for selecting appropriate perturbation schemes based on the expected Fisher information matrix with respect to the perturbation vector is proposed. It is shown that arbitrarily perturbing these models may result in misleading inference about the influential subjects. First-order influence measures for identifying the correct influential subjects and replicates on corrected score estimators are defined. We introduce different perturbation schemes including perturbation of subjects and replicates on the corrected likelihood function and obtain the density of the perturbed model from which the methodology is based. Particularly, three perturbation of variances schemes could be a better way to handle badly modeled subjects or replicates. Two real data sets are analyzed to illustrate the use of our local influence measures. Copyright Springer-Verlag Berlin Heidelberg 2014

Keywords: Local influence; Comparative calibration; Replicate measurement; Corrected score; Appropriate perturbation (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s00362-012-0489-3

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