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Titlebook: Applications of Linear and Nonlinear Models; Fixed Effects, Rando Erik Grafarend,Joseph Awange Book 20121st edition Springer-Verlag Berlin

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發(fā)表于 2025-3-21 17:35:50 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Applications of Linear and Nonlinear Models
副標(biāo)題Fixed Effects, Rando
編輯Erik Grafarend,Joseph Awange
視頻videohttp://file.papertrans.cn/587/586467/586467.mp4
概述Numerous geodetic examples and various test computations..The treatment of both linear and nonlinear geodetic problems side by side as done in the present book is rare to come by.The polynomial method
圖書(shū)封面Titlebook: Applications of Linear and Nonlinear Models; Fixed Effects, Rando Erik Grafarend,Joseph Awange Book 20121st edition Springer-Verlag Berlin
描述.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 as well as 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 overdeterimined 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 estimation by the so called E-D correspondence as well as its Bayes design. In addition, we discuss continuous networks versus discrete networks, use of Grassmann-Pluecker coordinates, criterion matrices of type Taylor-Karman as well as FUZZY sets. Chapter seven is a speciality in the tre
出版日期Book 20121st edition
關(guān)鍵詞BLUUE; Fixed effects; Geodesy; LESS; Linear Models; Nonlinear Models; Random effects; Statistics; Total leas
版次1
doihttps://doi.org/10.1007/978-3-642-22241-2
isbn_softcover978-3-662-50813-8
isbn_ebook978-3-642-22241-2
copyrightSpringer-Verlag Berlin Heidelberg 2012
The information of publication is updating

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The First Problem of Probabilistic Regression: The Bias Problem,geodetic application” (Statistical and Decision, Supplement Issue No. 2, pages 401–441, 105 references, Oldenbourg Verlag, München 1989), we collected 5 postulates for simultaneous determination of first and second central moments.
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Book 20121st editionoint of view is both an algebraic view as well as 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 regressi
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The Second Problem of Probabilistic Regression,uadratic unbiased estimators: QUE (b), invariant quadratic unbiased estimators: IQUE, (c) locally best, quadratic unbiased estimators, (d) locally best, invariant quadratic unbiased estimators, (e) best QUE and best IQUE, (f) quadratic unbiased estimators of minimum norm: MINQUE. The geodetic examples are reproduced here.
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