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Applications of Linear and Nonlinear Models: Fixed Effects, Random Effects, and Total Least Squares

Applications of Linear and Nonlinear Models: Fixed Effects, Random Effects, and Total Least Squares

Hardcover

Series: Springer Geophysics

AlgebraPhysicsProbability & Statistics

ISBN10: 3030945979
ISBN13: 9783030945978
Publisher: Springer
Published: Oct 2 2022
Pages: 1113
Weight: 4.35
Height: 1.80 Width: 6.20 Depth: 9.40
Language: English

This book provides numerous examples of linear and nonlinear model applications. Here, we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear regression models within the first 8 chapters. Our point of view is both an algebraic view and a stochastic one. For example, there is an equivalent lemma between a best, linear uniformly unbiased estimation (BLUUE) in a Gauss-Markov model and a least squares solution (LESS) in a system of linear equations. While BLUUE is a stochastic regression model, LESS is an algebraic solution. In the first six chapters, we concentrate on underdetermined and overdetermined linear systems as well as systems with a datum defect. We review estimators/algebraic solutions of type MINOLESS, BLIMBE, BLUMBE, BLUUE, BIQUE, BLE, BIQUE, and total least squares. The highlight is the simultaneous determination of the first moment and the second central moment of a probability distribution in an inhomogeneous multilinear estimationby the so-called E-D correspondence as well as its Bayes design. In addition, we discuss continuous networks versus discrete networks, use of Grassmann-Plucker coordinates, criterion matrices of type Taylor-Karman as well as FUZZY sets. Chapter seven is a speciality in the treatment of an overjet. This second edition adds three new chapters:

Also from

Grafarend, Erik W.

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Physics