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  • 标题:Estimation of mean form and mean form difference under elliptical laws
  • 本地全文:下载
  • 作者:José A. Díaz-García ; Francisco J. Caro-Lopera
  • 期刊名称:Electronic Journal of Statistics
  • 印刷版ISSN:1935-7524
  • 出版年度:2017
  • 卷号:11
  • 期号:1
  • 页码:2424-2460
  • DOI:10.1214/17-EJS1289
  • 语种:English
  • 出版社:Institute of Mathematical Statistics
  • 摘要:The matrix variate elliptical generalization of [30] is presented in this work. The published Gaussian case is revised and modified. Then, new aspects of identifiability and consistent estimation of mean form and mean form difference are considered under elliptical laws. For example, instead of using the Euclidean distance matrix for the consistent estimates, exact formulae are derived for the moments of the matrix $\mathbf{B}=\mathbf{X}^{c}\left(\mathbf{X}^{c}\right)^{T}$; where $\mathbf{X}^{c}$ is the centered landmark matrix. Finally, a complete application in Biology is provided; it includes estimation, model selection and hypothesis testing.
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