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Bayesian Analysis For Social Sciences

detailed descriptions of all the key concepts, without assuming any background in statistics beyond a first course. It features examples of how to;

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Bayesian Approaches in Oncology Using R and OpenBUGS

grow in statistical analysis. It intended to make a single source of information on Bayesian statistical methodology for oncology research to;

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A First Course in Bayesian Statistical Methods

A self-contained introduction to probability, exchangeability and Bayes' rule provides a theoretical understanding of the applied material;

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A First Course in Bayesian Statistical Methods

A self-contained introduction to probability, exchangeability and Bayes' rule provides a theoretical understanding of the applied material;

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An Introduction to Bayesian Inference, Methods and Computation

These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy;

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Introduction to Bayesian Statistics

of overviews and reviews of important tools used in Bayesian statistical methods. There is a strong upsurge in the use of Bayesian methods in applied;

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Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists

The first all-inclusive introduction to modern statistical research methods in the natural resource sciences The use of Bayesian;

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Bayesian Statistics for Experimental Scientists

This book offers an introduction to the Bayesian approach to statistical inference, with a focus on nonparametric and distribution-free;

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Statistical Bioinformatics with R

Statistical Bioinformatics provides a balanced treatment of statistical theory in the context of bioinformatics applications.

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Statistical Inference

Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian;

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Statistical Inference

Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian;

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Statistical Reliability Engineering

Proven statistical reliability analysis methods-available for the first time to engineers in the West While probabilistic methods of system;

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Bayesian Methods for Nonlinear Classification and Regression

Classification and Regression is the first book to bring together, in a consistent statistical framework, the ideas of nonlinear modelling and Bayesian;

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A Mathematical Primer for Social Statistics

A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods;

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Bayesian Inverse Problems

Gain a fundamental understanding of the use of probabilistic methods and reliability analysis techniques in engineering applications;

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Bayesian Analysis for Population Ecology

, modern Bayesian methods have become important in this area of statistical inference and forecasting. Emphasising model choice and model;

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Bayesian Analysis for Population Ecology

, modern Bayesian methods have become important in this area of statistical inference and forecasting. Emphasising model choice and model averaging;

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Computational Bayesian Statistics

a textbook for a first graduate-level course in Bayesian computation with a focus on Monte Carlo methods. The extensive discussion;

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Computational Bayesian Statistics

a textbook for a first graduate-level course in Bayesian computation with a focus on Monte Carlo methods. The extensive discussion;

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Bayesian Methods And Ethics In A Clinical Trial Design

This book discusses the ethical considerations of Bayesian methods applied to clinical trial design. It is comprised of essays written not;

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Statistical Methods for Reliability Data, Second Edition

An authoritative guide to the most recent advances in statistical methods for quantifying reliability Statistical Methods for;

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Bayesian Modeling in Bioinformatics

Bayesian kernel machines, and QTL mapping. Focusing on design, statistical inference, and data analysis from a Bayesian perspective, this volume;

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Bayesian Modeling in Bioinformatics

Bayesian kernel machines, and QTL mapping. Focusing on design, statistical inference, and data analysis from a Bayesian perspective, this volume;

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Statistical Intervals

easy-to-apply format Statistical intervals provide invaluable tools for quantifying sampling uncertainty. The widely hailed first edition;

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Bayesian Theory and Methods with Applications

, environmental sciences, business and economics and social sciences, among others. This book explores the use of Bayesian analysis in the statistical;

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Biostatistics

interpretive system integrating data with observation, the Bayesian approach provides a nuanced yet mathematically rigorous means of conceptualizing;

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Handbook of Approximate Bayesian Computation

first time in a single volume, the Handbook of Approximate Bayesian Computation (ABC) presents an extensive overview of the theory, practice and;

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