Estimation in High-Dimensional Analysis and Multivariate Linear Models

被引：3
|
作者：
Kollo, Tonu [3 ]
Von Rosen, Tatjana [2 ]
Von Rosen, Dietrich [1 ]
机构：
[1] Swedish Univ Agr Sci, Dept Engn & Technol, Uppsala, Sweden
[2] Stockholm Univ, Dept Stat, S-10691 Stockholm, Sweden
[3] Univ Tartu, Inst Math Sci, EE-50090 Tartu, Estonia
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2011年 / 40卷 / 07期
关键词：
Growth Curve model; High-dimensional analysis; Kolmogorov asymptotics; Parameter estimation; p/n; -asymptotics; GROWTH CURVE MODEL; COVARIANCE-MATRIX; POPULATION EIGENVALUES; FEWER OBSERVATIONS; WISHART MATRIX; TESTS; VARIANCE;
D O I：
10.1080/03610920903576556
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：
This article presents a new approach of estimating the parameters describing the mean structure in the Growth Curve model when the number of variables compared with the number of observations is large. An unbiased, consistent, and asymptotic normal estimator is derived as well as its.
引用
收藏
页码：1241 / 1253
页数：13
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