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Based on the problem how to model Seemingly Unrelated linear models with different batches of samples, the paper raises the method of getting rid of the stale and taking in the fresh. The method of taking in the fresh is that first, with a group of samples gotten to establish the linear model and receive least squares estimation; Second , the second batch of samples of data is received, re-use the...
This paper proposes a novel estimator named minimum-variance pseudo-unbiased reduced-rank estimator (MV- PURE) for the linear regression model, designed specially for the case where the model matrix is ill-conditioned and the unknown deterministic parameter vector to be estimated is subjected to known linear constraints. As a natural generalization of the Gauss-Markov (BLUE) estimator, the MV-PURE...
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