000			02593nam a2200253 4500
005			20250625103920.0
008			250623b |||||||| |||| 00| 0 eng d
020			_a9789811284908
040			_aCSL _cCSL
041			_2eng _aeng
084			_aB2871 R4 _qCSL
100			_aBerger, James O _eAuthor _9814337
245			_aObjective Bayesian Inference
260			_aNew Jersey : _bworld scientific, _c2024.
300			_axv, 364 p. _b: ill. _c; 25 cm.
500			_aIncludes biography, author index and Index
520			_aBayesian analysis is today understood to be an extremely powerful method of statistical analysis, as well an approach to statistics that is particularly transparent and intuitive. It is thus being extensively and increasingly utilized in virtually every area of science and society that involves analysis of data.A widespread misconception is that Bayesian analysis is a more subjective theory of statistical inference than what is now called classical statistics. This is true neither historically nor in practice. Indeed, objective Bayesian analysis dominated the statistical landscape from roughly 1780 to 1930, long before 'classical' statistics or subjective Bayesian analysis were developed. It has been a subject of intense interest to a multitude of statisticians, mathematicians, philosophers, and scientists. The book, while primarily focusing on the latest and most prominent objective Bayesian methodology, does present much of this fascinating history.The book is written for four different audiences. First, it provides an introduction to objective Bayesian inference for non-statisticians; no previous exposure to Bayesian analysis is needed. Second, the book provides an overview of the development and current state of objective Bayesian analysis and its relationship to other statistical approaches, for those with interest in the philosophy of learning from data. Third, the book presents a careful development of the particular objective Bayesian approach that we recommend, the reference prior approach. Finally, the book presents as much practical objective Bayesian methodology as possible for statisticians and scientists primarily interested in practical applications.
650			_aBayesian statistical decision theory _9814338
650			_aModels with special structures _9814339
650			_aoverall objective priors _9814340
700			_aM Bernardo, Jose _eCo-Author _9814341
700			_aSun, Dongchu _eCo-Author _9814342
942			_2CC _n0 _cTEXL _hB2871 R4
999			_c1432841 _d1432841