Bootstrapping data with multiple levels of variation

被引：10

作者：

Field, Christopher A. ^{[1
]}

Pang, Zhen ^{[2
,3
]}

Welsh, Alan H. ^{[3
]}

机构：

[1] Dalhousie Univ, Dept Math & Stat, Halifax, NS B3H 3J5, Canada

[2] Nanyang Technol Univ, Div Math Sci, Singapore 637371, Singapore

[3] Australian Natl Univ, Ctr Math & Applicat, Canberra, ACT 0200, Australia

来源：

CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE | 2008年 / 36卷 / 04期

基金：

澳大利亚研究理事会; 加拿大自然科学与工程研究理事会;

关键词：

Best linear unbiased prediction; hierarchical data; mixed model; quasi-likelihood estimation; random effect; unbalanced data;

D O I：

10.1002/cjs.5550360403

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：

The authors consider general estimators for the mean and variance parameters in the random effect model and in the transformation model for data with multiple levels of variation. They show that these estimators have different distributions under the two models unless all the variables have Gaussian distributions. They investigate the asymptotic properties of bootstrap procedures designed for the two models. They also report simulation results and illustrate the bootstraps using data on red spruce trees.

引用

页码：521 / 539

页数：19

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