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  • 标题:Global convergence and ascent property of a cyclic algorithm used for statistical analysis of crash data
  • 本地全文:下载
  • 作者:Issa Cherif Geraldo ; Assi N’Guessan ; Kossi Essona Gneyou
  • 期刊名称:Afrika Statistika
  • 印刷版ISSN:2316-090X
  • 出版年度:2018
  • 卷号:13
  • 期号:2
  • 页码:1631-1643
  • 语种:English
  • 出版社:African journals online
  • 摘要:In this paper, we consider an estimation algorithm called cyclic iterative algorithm (CA) that is used in statistics to estimate the unknown vector parameter of a crash data model. We provide a theoretical proof of the global convergence of the CA that justifies the good numerical results obtained in early numerical studies of this algorithm. We also prove that the CA is an ascent algorithm, what ensures its numerical stability.
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