Maximum Likelihood Estimation in Random Coefficient Models
作者:
WarrenT. Dent,
Clifford Hildreth,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1977)
卷期:
Volume 72,
issue 357
页码: 69-72
ISSN:0162-1459
年代: 1977
DOI:10.1080/01621459.1977.10479908
出版商: Taylor & Francis Group
关键词: Random coefficient models;Maximum likelihood estimation;Nonlinear optimization;Numerical accuracy
数据来源: Taylor
摘要:
Previous Monte Carlo studies examining properties of estimators in random coefficient models have been hindered in part by computational difficulties. In particular, determination of maximum likelihood estimators appears sensitive to the computational algorithm used. In a small Monte Carlo experiment, several distinctly motivated algorithms are examined with respect to accuracy and cost in searching for global and local maximum likelihood parameter estimates. A noncalculus oriented approach offers promise. When compared with other estimators, maximum likelihood estimators, so determined, appear to be statistically relatively efficient.
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