Published June 1980
| Version Submitted
Working Paper
Open
Exact and Approximate Distributions of the Maximum Likelihood Estimator of a Slope Coefficient: The LIML Estimator for a Known Covariance Matrix
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Abstract
When the errors are normally independently distributed with equal variance, the maximum likelihood estimator of the slope of a linear functional relationship is the slope of the line minimizing the sum of squared deviations orthogonal to the line. The exact density and distribution of this estimator are obtained. Approximate distributions are obtained, and their accuracies are discussed.
Additional Information
This work was supported in part by National Science Foundation Grant SOC77-14944 and SES79-13976 at the Institute for Mathematical Studies in the Social Sciences, Stanford University, and in part by NSF Grant SOC76-22232. The first author was a Sherman Fairchild Distinguished Scholar at the California Institute of Technology when this paper was completed. The authors are indebted to Naoto Kunitomo, Kimio Morimune, and Kanemi Ban for assistance in this research. Published as Anderson, T. W., and Takamitsu Sawa. "Exact and approximate distributions of the maximum likelihood estimator of a slope coefficient." Journal of the Royal Statistical Society. Series B (Methodological) (1982): 52-62.Attached Files
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Additional details
Identifiers
- Eprint ID
- 82265
- Resolver ID
- CaltechAUTHORS:20171010-150811357
Related works
- Describes
- http://resolver.caltech.edu/CaltechAUTHORS:20171120-132429675 (URL)
Funding
- NSF
- SOC77-14944
- NSF
- SES79-13976
- NSF
- SOC76-22232
- Sherman Fairchild Foundation
Dates
- Created
-
2017-10-11Created from EPrint's datestamp field
- Updated
-
2019-10-03Created from EPrint's last_modified field
Caltech Custom Metadata
- Caltech groups
- Social Science Working Papers
- Series Name
- Social Science Working Paper
- Series Volume or Issue Number
- 326