000			02563nam a22003618i 4500
001			CR9780511569678
003			UkCbUP
005			20200124160335.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			090520s1986||||enk o ||1 0|eng|d
020			_a9780511569678 (ebook)
020			_z9780521323802 (hardback)
020			_z9780521096034 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQ370 _b.M385 1984
082	0	0	_a001.53/9 _219
111	2		_aMaximum Entropy Workshop _n(4th : _d1984 : _cUniversity of Calgary)
245	1	0	_aMaximum entropy and Bayesian methods in applied statistics : _bproceedings of the Fourth Maximum Entropy Workshop, University of Calgary, 1984 / _cedited by James H. Justice.
246	3		_aMaximum Entropy & Bayesian Methods in Applied Statistics
264		1	_aCambridge : _bCambridge University Press, _c1986.
300			_a1 online resource (319 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
520			_aThis 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.
650		0	_aEntropy (Information theory) _vCongresses.
650		0	_aBayesian statistical decision theory _vCongresses.
700	1		_aJustice, James H., _d1941- _eeditor.
776	0	8	_iPrint version: _z9780521323802
856	4	0	_uhttps://doi.org/10.1017/CBO9780511569678
999			_c522905 _d522903