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  • 标题:Joint Estimation of Offspring Mean and Offspring Variance of Controlled Branching Process
  • 作者:Arpita Inamdar ; Mohan Kale
  • 期刊名称:Sankhya. Series A, mathematical statistics and probability
  • 印刷版ISSN:0976-836X
  • 电子版ISSN:0976-8378
  • 出版年度:2016
  • 卷号:78
  • 期号:2
  • 页码:248-268
  • DOI:10.1007/s13171-016-0082-2
  • 语种:English
  • 出版社:Indian Statistical Institute
  • 摘要:The paper discusses the joint estimation of two important parameters of the offspring distribution namely mean and variance of a controlled branching process or ϕ branching process. The estimation of these parameters was separately carried out by Gonzalez et al. ( Test , 13 (2), 465–479, ( 2004 ), Test , 14 (1), 199–213, ( 2005 )). The present article is an attempt to show that, the estimators proposed by these authors are also optimal in the sense of estimating functions ( O F optimality). The joint O A optimality, that is; joint asymptotic properties of these estimators are also established using martingale limit theory. The joint O A optimality in special case, a model proposed by Dion and Essebbar ( 1995 ) for controlled branching process is also discussed.
  • 关键词:Estimating equations ; Joint asymptotic normality ; Martingale convergence theorem ; Martingale central limit theorem
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