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Influence diagnostics in possibly asymmetric circular-linear multivariate regression models. (English) Zbl 06800590

Summary: Distributional studies and regression models have played important roles in statistical analysis of circular data. Asymmetric circular-linear multivariate regression models [A. SenGupta and F. I. Ugwuowo, “Asymmetric circular-linear multivariate regression models with applications to environmental data”, Environ. Ecol. Stat. 13, No. 3, 299–309 (2006; doi:10.1007/s10651-005-0013-1)] are motivated by and applied to predict some environmental characteristics based on both circular and linear predictors. In this paper, we consider a likelihood approach [R. D. Cook, J. R. Stat. Soc., Ser. B 48, 133–169 (1986; Zbl 0608.62041)] to study influence diagnostic analysis for these models, using the maximum likelihood estimation and influence diagnostics methods. The observed information matrices and normal curvatures are derived. Simulated and real data examples are then provided to illustrate our approach and establish the utility of our results.

MSC:

62J20 Diagnostics, and linear inference and regression
62J05 Linear regression; mixed models

Citations:

Zbl 0608.62041

Software:

CircStats; circular
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Full Text: DOI

References:

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