Object oriented data analysis: Sets of trees

被引:101
|
作者
Wang, Haonan [1 ]
Marron, J. S.
机构
[1] Colorado State Univ, Dept Stat, Ft Collins, CO 80523 USA
[2] Univ N Carolina, Dept Stat, Chapel Hill, NC 27599 USA
来源
ANNALS OF STATISTICS | 2007年 / 35卷 / 05期
关键词
functional data analysis; nonlinear data space; object oriented data analysis; population of tree-structured objects; principal component analysis;
D O I
10.1214/009053607000000217
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Object oriented data analysis is the statistical analysis of populations of complex objects. In the special case of functional data analysis, these data objects are curves, where standard Euclidean approaches, such as principal component analysis, have been very successful. Recent developments in medical image analysis motivate the statistical analysis of populations of more complex data objects which are elements of mildly non-Euclidean spaces, such as Lie groups and symmetric spaces, or of strongly non-Euclidean spaces, such as spaces of tree-structured data objects. These new contexts for object oriented data analysis create several potentially large new interfaces between mathematics and statistics. This point is illustrated through the careful development of a novel mathematical framework for statistical analysis of populations of tree-structured objects.
引用
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页码:1849 / 1873
页数:25
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