Abstract
This chapter derives the two fundamental linear estimators: Section 3.1: The non-Bayesian linear least-squares estimator Section 3.2: The Bayesian linear least-squares estimator Throughout this chapter we concern ourselves with the derivation of algebraic estimators \(\underline{\hat{z}}\) for some random vector \(\underline{z}\), but ignoring the issues of what \(\underline{z}\) represents, or any concerns regarding its size, both of which are extremely important and are examined closely beginning with Chapter 5.
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© 2011 Springer New York
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Fieguth, P. (2011). Static Estimation and Sampling. In: Statistical Image Processing and Multidimensional Modeling. Information Science and Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7294-1_3
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DOI: https://doi.org/10.1007/978-1-4419-7294-1_3
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Online ISBN: 978-1-4419-7294-1
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