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  • 标题:Influence Diagnostics in Possibly Asymmetric Circular-Linear Multivariate Regression Models
  • 本地全文:下载
  • 作者:S. Liu ; T. Ma ; A. SenGupta
  • 期刊名称:Sankhya. Series B, applied and interdisciplinary statistics
  • 印刷版ISSN:0976-8386
  • 电子版ISSN:0976-8394
  • 出版年度:2017
  • 卷号:79
  • 期号:1
  • 页码:76-93
  • DOI:10.1007/s13571-016-0116-8
  • 语种:English
  • 出版社:Indian Statistical Institute
  • 摘要:Abstract Distributional studies and regression models have played important roles in statistical analysis of circular data. Asymmetric circular-linear multivariate regression models (SenGupta and Ugwuowo Environ. Ecol. Stat. 13(3), 299–309 2006) 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 (Cook J. R. Stat. Soc. Ser. B Stat Methodol. 48(2), 133–169 1986) 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.
  • 关键词:Keywords and phrasesEnAngular-linear dependencyMaximum likelihood estimationSimulation studySolar energy data
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