Maximum entropy and Bayesian methods in applied statistics : proceedings of the Fourth Maximum Entropy Workshop, University of Calgary, 1984 / edited by James H. Justice.
Maximum Entropy Workshop (4th : 1984 : University of Calgary)| Call Number | 001.53/9 |
| Author | Maximum Entropy Workshop 1984 : University of Calgary) |
| Title | Maximum entropy and Bayesian methods in applied statistics : proceedings of the Fourth Maximum Entropy Workshop, University of Calgary, 1984 / edited by James H. Justice. Maximum Entropy & Bayesian Methods in Applied Statistics |
| Physical Description | 1 online resource (319 pages) : digital, PDF file(s). |
| Notes | Title from publisher's bibliographic system (viewed on 05 Oct 2015). |
| Summary | This collection of papers by leading researchers in their respective fields contains contributions showing the use of the maximum entropy method in many of the fields in which it finds application. In the physical, mathematical and biological sciences it is often necessary to make inferences based on insufficient data. The problem of choosing one among the many possible conclusions or models which are compatible with the data may be resolved in a variety of ways. A particularly appealing method is to choose the solution which maximizes entropy in the sense that the conclusion or model honours the observed data but implies no further assumptions not warranted by the data. The maximum entropy principle has been growing in importance and acceptance in many fields, perhaps most notably statistical physics, astronomy, geophysics, signal processing, image analysis and physical chemistry. The papers included in this volume touch on most of the current areas of research activity and application, and will be of interest to research workers in all fields in which the maximum entropy method may be applied. |
| Added Author | Justice, James H., 1941- editor. |
| Subject | Entropy (Information theory) Congresses. Bayesian statistical decision theory Congresses. |
| Multimedia |
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| Summary | This collection of papers by leading researchers in their respective fields contains contributions showing the use of the maximum entropy method in many of the fields in which it finds application. In the physical, mathematical and biological sciences it is often necessary to make inferences based on insufficient data. The problem of choosing one among the many possible conclusions or models which are compatible with the data may be resolved in a variety of ways. A particularly appealing method is to choose the solution which maximizes entropy in the sense that the conclusion or model honours the observed data but implies no further assumptions not warranted by the data. The maximum entropy principle has been growing in importance and acceptance in many fields, perhaps most notably statistical physics, astronomy, geophysics, signal processing, image analysis and physical chemistry. The papers included in this volume touch on most of the current areas of research activity and application, and will be of interest to research workers in all fields in which the maximum entropy method may be applied. |
| Notes | Title from publisher's bibliographic system (viewed on 05 Oct 2015). |
| Subject | Entropy (Information theory) Congresses. Bayesian statistical decision theory Congresses. |
| Multimedia |