
Bayesian Methods by Thomas Leonard
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.-
Data Analysis and Graphics Using R
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Measure Theory and Filtering
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Essentials of Statistical Inference
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Markov Chains
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Applied Asymptotics
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A User's Guide to Measure Theoretic Probability
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Probability
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High-Dimensional Probability
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Asymptotic Statistics
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Statistical Models
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Model Selection and Model Averaging
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Bootstrap Methods and their Application
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Random Graph Dynamics
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Modern Statistical Methods and Theory
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A Course in Interacting Particle Systems
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Networks
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The Coordinate-Free Approach to Linear Models
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The Estimation and Tracking of Frequency
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Semiparametric Regression
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Statistical Mechanics of Disordered Systems
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Random Networks for Communication
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Statistical Analysis of Stochastic Processes in Time
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Regression for Categorical Data
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Numerical Methods of Statistics
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Symmetry Studies
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Nonparametric Estimation under Shape Constraints
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Elements of Distribution Theory
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From Finite Sample to Asymptotic Methods in Statistics
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Design of Comparative Experiments
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Analysis of Multivariate and High-Dimensional Data
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Mathematical Foundations of Infinite-Dimensional Statistical Models
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Probability on Trees and Networks
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Spectral Analysis for Univariate Time Series
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Predictive Statistics
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Long-Range Dependence and Self-Similarity
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Statistical Hypothesis Testing in Context: Volume 52
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Saddlepoint Approximations with Applications
'… challenging and worthwhile … this book is a very welcome and original contribution to the literature on Bayesian statistics' J. V. Zidek, ISI Short Book Reviews
'The book makes interesting reading and the breadth of ideas tackled by the authors is enormous … deserves a place in the university library as well as in the personal libraries of researchers who are interested in the Bayesian approach.' Carmen Fernández, The Statistician
'The book is highly recommended as a well written intermediate book on some modern topics of Bayesian analysis.' H. K. van Dijk, Niew Archief voor Wiskunde
'The explanations stated in the book are very clear, the detailed computations, and the particular way of describing problems, theorems and applications in this book make it useful into only for statisticians but also for other researchers who are confronted with problems of data analysis and who are not primarily familiar with statistical methods.' Monatshefte für Mathematik
'A very readable and interesting book.' Indian Journal of Statistics
'The book makes interesting reading and the breadth of ideas tackled by the authors is enormous … deserves a place in the university library as well as in the personal libraries of researchers who are interested in the Bayesian approach.' Carmen Fernández, The Statistician
'The book is highly recommended as a well written intermediate book on some modern topics of Bayesian analysis.' H. K. van Dijk, Niew Archief voor Wiskunde
'The explanations stated in the book are very clear, the detailed computations, and the particular way of describing problems, theorems and applications in this book make it useful into only for statisticians but also for other researchers who are confronted with problems of data analysis and who are not primarily familiar with statistical methods.' Monatshefte für Mathematik
'A very readable and interesting book.' Indian Journal of Statistics
| SKU | Unavailable |
| ISBN 13 | 9780521594172 |
| ISBN 10 | 0521594170 |
| Title | Bayesian Methods |
| Author | Thomas Leonard |
| Series | Cambridge Series In Statistical And Probabilistic Mathematics |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Cambridge University Press |
| Year published | 1999-06-13 |
| Number of pages | 348 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |




































