Inequality Constrained Least-Squares Estimation
作者:
ChongKiew Liew,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1976)
卷期:
Volume 71,
issue 355
页码: 746-751
ISSN:0162-1459
年代: 1976
DOI:10.1080/01621459.1976.10481560
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
There are growing demands to use prior and sample information for parameter estimation of a regression model in order to maintain consistency with underlying theory. To meet such demands, this paper provides an inequality constrained least-squares (ICLS) estimation, specifies an untruncated variance-covariance matrix of the ICLS estimates, and discusses their statistical properties in large-and small-sample cases. Finally, the ICLS and the ordinary least-squares OLS estimates are compared in terms of sample bias, sample mean-square error MSE and sample variance of the estimates by a Monte Carlo study.
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