| 期刊全称 | Applications of Linear and Nonlinear Models | | 期刊简称 | Fixed Effects, Rando | | 影响因子2023 | Erik W. Grafarend,Silvelyn Zwanzig,Joseph L. Awang | | 视频video | | | 发行地址 | Provides numerous examples of linear and nonlinear model applications.Gives simple and elaborate explanations.Presents rigorous treatment of integer least squares, Bayes, and error-in-variable topics | | 学科分类 | Springer Geophysics | | 图书封面 |  | | 影响因子 | .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 Tay | | Pindex | Book 2022Latest edition |
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发表于 2025-3-21 19:48:21
