Prediction in the linear model under a linear constraint

In this paper we determine the Gauss–Markov predictor of the nonobservable part of a random vector satisfying the linear model under a linear constraint.

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Bibliographic Details
Published in:Advances in statistical analysis : AStA : a journal of the German Statistical Society 2008-05, Vol.92 (2), p.207-215
Main Authors: Kloberdanz, Kathrin, Schmidt, Klaus D.
Format: Article
Language:English
Subjects:
Econometrics
Economics
Finance
Insurance
Management
Mathematics and Statistics
Original Paper
Probability Theory and Stochastic Processes
Statistics
Statistics for Business
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Summary:In this paper we determine the Gauss–Markov predictor of the nonobservable part of a random vector satisfying the linear model under a linear constraint.
ISSN:1863-8171
1863-818X
DOI:10.1007/s10182-008-0062-5