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|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.|
|Citation:||Chemometrics And Intelligent Laboratory Systems. Elsevier, v. 156, p. 21 - 35, 2016.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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