Parameter Estimation in Linear Models

Karl-Rudolf Koch
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Karl-Rudolf Koch: Institute of Theoretical Geodesy of the University of Bonn

Chapter 3 in Parameter Estimation and Hypothesis Testing in Linear Models, 1999, pp 149-269 from Springer

Abstract: Abstract The linear models for estimating parameters are so composed that the expected values of the observations, which are carried out for the estimation of the parameters and which represent random variables, are expressed as linear functions of the unknown parameters. The coefficients of the linear functions are assumed to be known. The estimation of parameters in linear models therefore means essentially the estimation of the expected values of the observations.

Keywords: Covariance Matrix; Unknown Parameter; Normal Equation; Unbiased Estimator; Gaussian Elimination (search for similar items in EconPapers)
Date: 1999
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DOI: 10.1007/978-3-662-03976-2_4

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