Constrained Least Squares Estimation and ANOVA

Dale L. Zimmerman
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Dale L. Zimmerman: University of Iowa, Department of Statistics and Actuarial Science

Chapter 10 in Linear Model Theory, 2020, pp 201-237 from Springer

Abstract: Abstract In our consideration of least squares estimation up to this point, β was unrestricted, i.e., β could assume any value in ℝ p $$\mathbb {R}^p$$ . We now consider least squares estimation for models in which β is restricted to the subset of ℝ p $$\mathbb {R}^p$$ consisting of all those β-values that satisfy the consistent system of linear equations A β = h , $$\displaystyle \mathbf {A}\boldsymbol {\beta } = \mathbf {h}, $$ where A is a specified q × p matrix of rank q ∗ and h is a specified q-vector.

Date: 2020
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DOI: 10.1007/978-3-030-52063-2_10

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