Local Influence in Regression Models with Measurement Errors and Censored Data Considering the Student–t Distribution

Alejandro Monzón Montoya ()
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Alejandro Monzón Montoya: Universidade Federal de Minas Gerais

Sankhya B: The Indian Journal of Statistics, 2024, vol. 86, issue 1, No 4, 108 pages

Abstract: Abstract In this paper, the local influence approach is studied in regression models with measurement errors for multivariate censored responses under the Student-t distribution. The multivariate Student–t distribution and the multivariate normal, distributions of the independent normal class, are studied and used to compare various measuring instruments. The ECM algorithm is used to obtain maximum likelihood estimates of the model parameters and using the log-likelihood function of the complete data we obtain measures of local influence based on the methodology proposed by Zhu and Lee (Journal of the Royal Statistical Society, Series B 63:121–126, 2001) and Lee and Xu (Computational Statistics and Data Analysis 45:321–341, 2004). Finally, the described methodologies are used in real data analysis that illustrates the usefulness of the approach.

Keywords: Censored data; ECM algorithm; measurement error models; student–t distribution; Primary 62J20; Secondary 62N01 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13571-023-00316-6

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