Bayesian Methods: An Analysis for Statisticians and Interdisciplinary Researchers

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Cambridge University Press, 1999 - Mathematics - 333 pages
1 Review
This book describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students. It is unusual in presenting Bayesian statistics with a practical flavor and an emphasis on mainstream statistics, showing how to infer scientific, medical, and social conclusions from numerical data. The authors draw on many years of experience with practical and research programs and describe many statistical methods, not readily available elsewhere. A first chapter on Fisherian methods, together with a strong overall emphasis on likelihood, makes the text suitable for mainstream statistics courses whose instructors wish to follow mixed or comparative philosophies. The other chapters contain important sections relating to many areas of statistics such as the linear model, categorical data analysis, time series and forecasting, mixture models, survival analysis, Bayesian smoothing, and non-linear random effects models. The text includes a large number of practical examples, worked examples, and exercises. It will be essential reading for all statisticians, statistics students, and related interdisciplinary researchers.
 

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Contents

I
1
II
6
III
19
IV
33
V
42
VI
45
VII
63
VIII
66
XXXII
165
XXXIII
166
XXXIV
172
XXXV
176
XXXVI
179
XXXVII
182
XXXVIII
185
XXXIX
187

IX
68
XI
69
XII
75
XIII
76
XIV
81
XV
82
XVI
86
XVII
88
XVIII
91
XIX
92
XX
96
XXI
98
XXII
99
XXIII
105
XXIV
117
XXV
130
XXVI
134
XXVII
142
XXVIII
143
XXIX
155
XXX
157
XXXI
163
XL
189
XLI
190
XLII
217
XLIII
233
XLIV
237
XLV
238
XLVI
239
XLVII
240
XLVIII
242
XLIX
243
L
253
LI
259
LII
275
LIII
281
LIV
295
LVI
297
LVII
300
LVIII
303
LIX
321
LX
326
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