000			01826cam a22002294a 4500
008			100314s2003 000 0 eng
020			_a9780521734493
035			_a(Sirsi) u4916
040			_aEG-CaNU _C EG-CaNU _C EG-CaNU
042			_ancode
082	0	4	_a519.5 _2 22
100	1		_aDavison, A. C. _9636
245	1	0	_aStatistical Models.
260			_aCambridge, U.K. ; _aNew York : _bCambridge University Press, _c2003.
300			_ax, 726 p. : _bill. ; _c27 cm.
490	1		_aCambridge series in statistical and probabilistic mathematics
504			_aIncludes bibliographical references (p. 699-711) and indexes.
505	0		_a1. Introduction; 2. Variation; 3. Uncertainty; 4. Likelihood; 5. Models; 6. Stochastic models; 7. Estimation and hypothesis testing; 8. Linear regression models; 9. Designed experiments; 10. Nonlinear regression models; 11. Bayesian models; 12. Conditional and marginal inference.
520			_aModels and likelihood are the backbone of modern statistics. This 2003 book gives an integrated development of these topics that blends theory and practice, intended for advanced undergraduate and graduate students, researchers and practitioners. Its breadth is unrivaled, with sections on survival analysis, missing data, Markov chains, Markov random fields, point processes, graphical models, simulation and Markov chain Monte Carlo, estimating functions, asymptotic approximations, local likelihood and spline regressions as well as on more standard topics such as likelihood and linear and generalized linear models. Each chapter contains a wide range of problems and exercises. Practicals in the S language designed to build computing and data analysis skills, and a library of data sets to accompany the book, are available over the Web.
650		0	_aStatistics. _99797
596			_a1
999			_c3918 _d3918