A FIRST COURSE IN BAYESIAN STATISTICAL METHODS SPRINGER TEXTS IN STATISTICS

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A First Course In Bayesian Statistical Methods

Author : Peter D. Hoff
ISBN : 0387924078
Genre : Mathematics
File Size : 69.11 MB
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A self-contained introduction to probability, exchangeability and Bayes’ rule provides a theoretical understanding of the applied material. Numerous examples with R-code that can be run "as-is" allow the reader to perform the data analyses themselves. The development of Monte Carlo and Markov chain Monte Carlo methods in the context of data analysis examples provides motivation for these computational methods.
Category: Mathematics

Methods In Neuroethological Research

Author : Hiroto Ogawa
ISBN : 9784431543312
Genre : Medical
File Size : 73.72 MB
Format : PDF, ePub
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The rapid progress of neuroscience in the last decade can be largely attributed to significant advances in neuroethology, a branch of science that seeks to understand the neural basis of natural animal behavior. Novel approaches including molecular biological techniques, optical recording methods, functional anatomy, and informatics have brought drastic changes in how the neural systems underlying high-level behaviors such as learning and memory are described. This book introduces recent research techniques in neuroethology, with diverse topics involving nematodes, insects, and vertebrates (birds, mice and primates), divided into sections by research method. Each section consists of two chapters written by different authors who have developed their own unique approaches. Reports of research in “model animals” including C. elegans, Drosophila, and mice, which were not typical specimens in conventional neuroethology, have been deliberately selected for this book because a molecular genetic approach to these animals is necessary for advances in neuroethology. Novel methodology including optical recording and functional labeling with reporter genes such as GFP has been actively used in recent neurobiological studies, and genetic manipulation techniques such as optogenetics also are powerful tools for understanding the molecular basis of neural systems for animal behavior. This book provides not only these new strategies but also thought-provoking statements of philosophy in neuroethology for students and young researchers in the biological sciences.
Category: Medical

Safety Reliability Risk And Life Cycle Performance Of Structures And Infrastructures

Author : George Deodatis
ISBN : 9781315884882
Genre : Technology & Engineering
File Size : 29.25 MB
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Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures contains the plenary lectures and papers presented at the 11th International Conference on STRUCTURAL SAFETY AND RELIABILITY (ICOSSAR2013, New York, NY, USA, 16-20 June 2013), and covers major aspects of safety, reliability, risk and life-cycle performance of str
Category: Technology & Engineering

Monte Carlo Statistical Methods

Author : Christian Robert
ISBN : 9781475730715
Genre : Mathematics
File Size : 76.7 MB
Format : PDF
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We have sold 4300 copies worldwide of the first edition (1999). This new edition contains five completely new chapters covering new developments.
Category: Mathematics

An Introduction To Bayesian Analysis

Author : Jayanta K. Ghosh
ISBN : 9780387354330
Genre : Mathematics
File Size : 67.98 MB
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This is a graduate-level textbook on Bayesian analysis blending modern Bayesian theory, methods, and applications. Starting from basic statistics, undergraduate calculus and linear algebra, ideas of both subjective and objective Bayesian analysis are developed to a level where real-life data can be analyzed using the current techniques of statistical computing. Advances in both low-dimensional and high-dimensional problems are covered, as well as important topics such as empirical Bayes and hierarchical Bayes methods and Markov chain Monte Carlo (MCMC) techniques. Many topics are at the cutting edge of statistical research. Solutions to common inference problems appear throughout the text along with discussion of what prior to choose. There is a discussion of elicitation of a subjective prior as well as the motivation, applicability, and limitations of objective priors. By way of important applications the book presents microarrays, nonparametric regression via wavelets as well as DMA mixtures of normals, and spatial analysis with illustrations using simulated and real data. Theoretical topics at the cutting edge include high-dimensional model selection and Intrinsic Bayes Factors, which the authors have successfully applied to geological mapping. The style is informal but clear. Asymptotics is used to supplement simulation or understand some aspects of the posterior.
Category: Mathematics

Mathematical Reviews

Author :
ISBN : UOM:39015078588624
Genre : Mathematics
File Size : 61.8 MB
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Category: Mathematics

Bayesian Core A Practical Approach To Computational Bayesian Statistics

Author : Jean-Michel Marin
ISBN : 9780387389790
Genre : Computers
File Size : 53.51 MB
Format : PDF, Kindle
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This Bayesian modeling book is intended for practitioners and applied statisticians looking for a self-contained entry to computational Bayesian statistics. Focusing on standard statistical models, it provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical justifications.
Category: Computers

Essential Statistical Inference

Author : Dennis D. Boos
ISBN : 9781461448181
Genre : Mathematics
File Size : 61.87 MB
Format : PDF
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​This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems. An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology. Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods. ​
Category: Mathematics