Please use this identifier to cite or link to this item:
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
Date Issue: 2016
Appears in Collections:Unicamp - Artigos e Outros Documentos

Files in This Item:
File SizeFormat 
2-s2.0-84969916851.pdf1.13 MBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.