Missing Variables in Bayesian Regression II.
ResearchPublished 1975
We are concerned with the problem of parameter estimation in normal regression when some of the observations are missing. A Bayesian approach with vague prior distributions is taken. No assumption is made about the independent variables for which no observations are missing, but the missing components are assumed to be normally distributed with a mean that can depend on the other variables. Joint estimators of the parameters are obtained as the joint mode of the posterior distribution. 10 pp. Ref.
Document Details
- Copyright: RAND Corporation
- Availability: Available
- Year: 1975
- Print Format: Paperback
- Paperback Pages: 10
- Paperback Price: $20.00
- Document Number: P-5446
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Press, S. James and A. J. Scott, Missing Variables in Bayesian Regression II. RAND Corporation, P-5446, 1975. As of September 5, 2024: https://www.rand.org/pubs/papers/P5446.html
Press, S. James and A. J. Scott, Missing Variables in Bayesian Regression II. Santa Monica, CA: RAND Corporation, 1975. https://www.rand.org/pubs/papers/P5446.html. Also available in print form.
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