000			01979cam a22003858i 4500
001			22992132
003			OSt
005			20231227124154.0
008			230228s2023 enk b 001 0 eng
010			_a 2023002178
020			_a9781009098502 (hardback)
040			_aDLC _beng _erda _cDLC
042			_apcc
082	0	0	_a001.422
100	1		_aPressé, Steve, _eauthor.
245	1	0	_aData modeling for the sciences : _bapplications, basics, computations / _cSteve Pressé, Ioannis Sgouralis.
263			_a2306
264		1	_aCambridge ; _aNew York, NY : _bCambridge University Press, _c©2023.
300			_axii, 415 pages _c25 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
505	0		_aProbabilistic modeling and inference -- Dynamical systems and Markov processes -- Likelihoods and latent variables -- Bayesian inference -- Computational inference -- Regression models -- Mixture models -- Hidden Markov models -- State-space models -- Continuous time models.
520			_a"This accessible guide to data modeling introduces basic probabilistic concepts, gradually building toward state-of-the art data modeling and analysis techniques. Aimed at students and researchers in the sciences, the text is self-contained and pedagogical, including practical examples and end of chapter problems"-- _cProvided by publisher.
650		0	_aResearch _xStatistical methods.
650		0	_aScience _xStatistical methods.
650		0	_aProbabilities.
650		0	_aMathematical statistics.
700	1		_aSgouralis, Ioannis, _eauthor.
776	0	8	_iOnline version: _aPressé, Steve. _tData modeling for the sciences _dCambridge ; New York, nY : Cambridge University Press, 2023 _z9781009089555 _w(DLC) 2023002179
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK _n0
999			_c484916 _d484916