Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/319501
Type: Artigo de periódico
Title: Heavy Tailed Calibration Model With Berkson Measurement Errors For Replicated Data
Abstract: This work considers the so called controlled calibration model in which the independent variable is a controlled variable (Berkson type) and assumes that the measurement errors follow a scale mixtures of normal (SMN) distribution. The SMN family of distributions is an attractive class of symmetric distributions including the normal, Student-t, slash and contaminated normal distributions as special cases, providing a robust alternative to estimation in controlled calibration models in the absence of normality. An EM-type algorithm is developed, which is used to develop the local influence approach to assess the robustness aspects of the parameter estimates under four perturbation schemes. Results obtained from a real dataset in the area of chemistry are reported. © 2016 Elsevier B.V.
Editor: Elsevier
Citation: Chemometrics And Intelligent Laboratory Systems. Elsevier, v. 156, p. 21 - 35, 2016.
Rights: fechado
Identifier DOI: 10.1016/j.chemolab.2016.04.014
Address: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969916851&partnerID=40&md5=9e355b79bec25155ee585fe02f9f5fa9
Date Issue: 2016
Appears in Collections:Unicamp - Artigos e Outros Documentos

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