A Delta Method for Implicitly Defined Random Variables
作者:
Jacques Benichou,
MitchellH. Gail,
期刊:
The American Statistician
(Taylor Available online 1989)
卷期:
Volume 43,
issue 1
页码: 41-44
ISSN:0003-1305
年代: 1989
DOI:10.1080/00031305.1989.10475608
出版商: Taylor & Francis Group
关键词: Asymptotic methods;Asymptotic normality;Attributable risk;Implicit function;Taylor series variance calculations
数据来源: Taylor
摘要:
If random variables in one set are defined as explicit functions of random variables in a second set, Taylor series expansion (the delta method) may be used to prove the asymptotic normality of the first set of variates, under appropriate conditions, and to develop needed covariance estimates. Similar results are obtained for a set of random variables that are defined implicitly as functions of a second set of variables. This approach is used to calculate the variance of the attributable risk from case-control data.
点击下载:
PDF (404KB)
返 回