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Titlebook: Maximum-Entropy and Bayesian Methods in Science and Engineering; Foundations Gary J. Erickson,C. Ray Smith Book 1988 Springer Science+Busin

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發(fā)表于 2025-3-21 16:18:06 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Maximum-Entropy and Bayesian Methods in Science and Engineering
副標題Foundations
編輯Gary J. Erickson,C. Ray Smith
視頻videohttp://file.papertrans.cn/628/627922/627922.mp4
叢書名稱Fundamental Theories of Physics
圖書封面Titlebook: Maximum-Entropy and Bayesian Methods in Science and Engineering; Foundations Gary J. Erickson,C. Ray Smith Book 1988 Springer Science+Busin
描述This volume has its origin in the Fifth, Sixth and Seventh Workshops on and Bayesian Methods in Applied Statistics", held at "Maximum-Entropy the University of Wyoming, August 5-8, 1985, and at Seattle University, August 5-8, 1986, and August 4-7, 1987. It was anticipated that the proceedings of these workshops would be combined, so most of the papers were not collected until after the seventh workshop. Because all of the papers in this volume are on foundations, it is believed that the con- tents of this volume will be of lasting interest to the Bayesian community. The workshop was organized to bring together researchers from different fields to critically examine maximum-entropy and Bayesian methods in science and engineering as well as other disciplines. Some of the papers were chosen specifically to kindle interest in new areas that may offer new tools or insight to the reader or to stimulate work on pressing problems that appear to be ideally suited to the maximum-entropy or Bayesian method. A few papers presented at the workshops are not included in these proceedings, but a number of additional papers not presented at the workshop are included. In particular, we are delighted
出版日期Book 1988
關(guān)鍵詞Estimator; Information; Maximum entropy method; Probability space; complexity; entropy; logic
版次1
doihttps://doi.org/10.1007/978-94-009-3049-0
isbn_softcover978-94-010-7871-9
isbn_ebook978-94-009-3049-0Series ISSN 0168-1222 Series E-ISSN 2365-6425
issn_series 0168-1222
copyrightSpringer Science+Business Media Dordrecht 1988
The information of publication is updating

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Excerpts from Bayesian Spectrum Analysis and Parameter Estimation,lude other parameters such as decay and chirp. Results are given for computer simulated data and for real data ranging from magnetic resonance to astronomy to economic cycles. We find substantial improvements in resolution over Fourier transform methods.
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Understanding Ignorance,ernative theory of probability arose in practice to handle situations when there was relevant prior information concerning the problem under scrutiny or when repeated trials were practically or theoretically impossible to perform.
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The Axioms of Maximum Entropy,imum entropy applies directly to physical distributions other than probabilities. Furthermore, maximum entropy should also be used to select “best” parameters if the underlying model m has such freedom.
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,The Evolution of Carnot’s Principle,ions are easily recognized in the methods for predicting equilibrium conditions introduced by Gibbs in 1875. Chemical thermodynamics has been based on them ever since. What is new in this field is not the method, but the recognition of its generality.
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Book 1988ersity of Wyoming, August 5-8, 1985, and at Seattle University, August 5-8, 1986, and August 4-7, 1987. It was anticipated that the proceedings of these workshops would be combined, so most of the papers were not collected until after the seventh workshop. Because all of the papers in this volume ar
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0168-1222 y the University of Wyoming, August 5-8, 1985, and at Seattle University, August 5-8, 1986, and August 4-7, 1987. It was anticipated that the proceedings of these workshops would be combined, so most of the papers were not collected until after the seventh workshop. Because all of the papers in this
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Maximum-Entropy and Bayesian Methods in Science and EngineeringFoundations
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