Saddlepoint approximation in the linear structural relationship model
作者:
Spiridon Penev,
期刊:
Communications in Statistics - Simulation and Computation
(Taylor Available online 1995)
卷期:
Volume 24,
issue 2
页码: 349-366
ISSN:0361-0918
年代: 1995
DOI:10.1080/03610919508813246
出版商: Marcel Dekker, Inc.
关键词: Saddlepoint approximation;Linear structural relationship;Maximum likelihood estimator;M- estimator;marginal distribution
数据来源: Taylor
摘要:
It is shown that the joint maximum likelihood estimator of slope and intercept of the regression line in the classical (known error-variance ratio) linear structural relationship model can be represented as a solution of a two- dimensional M- equation. Therefore, it is possible to use a general saddlepoint approximation for multidimensional M- equations. Under normality assumptions we express the solution of the implicit multivariate “centering equation” in an explicit form. This allows a considerable saving of computing time. By integrating out numerically an unwanted variable one is also able to find the saddlepoint approximation for the slope- estimator. Numerical examples illustrate the efficiency of the approximation.
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