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Presenting an integrated look at the two main schools of statistical thought: the frequentist and the Bayesian, this book's main purpose is to show the parallels existing between the results given by both methodologies. The two schools are compared, contrasted and examined in the light of the most recent developments in theoretical and applied statistics research. This book is also an update on the field of statistics in general, with discussions of new research using approximation and computationally-intensive methods. From the graduate level, to those working in the related areas of Economics, Mathematics and Engineering this volume is a much needed guide to an integrated view of Statistics.
both Professors at the Federal University of Rio de Janerio
Preface
1. Introduction
2. Elements of inference
3. Prior distribution
4. Estimation
5. Approximate and computationally intensive methods
6. Hypothesis testing
7. Prediction
8. Introduction to linear models Sketched solutions to selected exercises List of distributions References Author index Subject index
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