000			01960nam a22003378i 4500
001			CR9780511802454
003			UkCbUP
005			20200124160247.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			101021s2007||||enk o ||1 0|eng|d
020			_a9780511802454 (ebook)
020			_z9780521850575 (hardback)
020			_z9780521615594 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQH541.2 _b.M38 2007
082	0	0	_a577.072/4 _222
100	1		_aMcCarthy, Michael A., _d1968- _eauthor.
245	1	0	_aBayesian methods for ecology / _cMichael A. McCarthy.
264		1	_aCambridge : _bCambridge University Press, _c2007.
300			_a1 online resource (xiii, 296 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			_aThe interest in using Bayesian methods in ecology is increasing, however many ecologists have difficulty with conducting the required analyses. McCarthy bridges that gap, using a clear and accessible style. The text also incorporates case studies to demonstrate mark-recapture analysis, development of population models and the use of subjective judgement. The advantages of Bayesian methods, are also described here, for example, the incorporation of any relevant prior information and the ability to assess the evidence in favour of competing hypotheses. Free software is available as well as an accompanying web-site containing the data files and WinBUGS codes. Bayesian Methods for Ecology will appeal to academic researchers, upper undergraduate and graduate students of Ecology.
650		0	_aEcology _xResearch _xStatistical methods.
650		0	_aBayesian statistical decision theory.
776	0	8	_iPrint version: _z9780521850575
856	4	0	_uhttps://doi.org/10.1017/CBO9780511802454
999			_c519055 _d519053