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Case Studies in Bayesian Statistical Modelling and Analysis

in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: * Illustrates how to do Bayesian analysis;

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Applied Bayesian Modelling

is the follow-up to the author's best selling book, Bayesian Statistical Modelling, and focuses on the potential applications of Bayesian;

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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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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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Multivariate Statistical Modelling Based on Generalized Linear Models

in statistics and data analysis. This second edition is extensively revised, especially those sections relating with Bayesian concepts.;

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Bayesian Approach To Intrepreting Archaeological Data

assume relatively little previous statistical or mathematical knowledge. Introducing the idea underlying the Bayesian approach to the statistical;

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Bayesian Hierarchical Models

collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian;

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Bayesian Hierarchical Models

collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian;

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Bayesian Statistical Modelling

programs.Bayesian Statistical Modelling is ideal for researchers in applied statistics, medical science, public health and the social;

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Handbook of Approximate Bayesian Computation

application of ABC methods. These simple, but powerful statistical techniques, take Bayesian statistics beyond the need to specify overly simplified;

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Bayesian Networks

Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility;

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Bayesian Thinking, Modeling and Computation

This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application;

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Bayesian Statistics and Quality Modelling in the Agro-Food Production Chain

uncertainty in modelling by using Bayesian statistics and Bayesian Belief Networks. Bayesian approaches use prior probabilities (partly accounting for;

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Flexible Bayesian Regression Modelling

Flexible Bayesian Regression Modeling is a step-by-step guide to the Bayesian revolution in regression modeling, for use in advanced;

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Survival Analysis with Interval-Censored Data

Leuven. His research interests include Bayesian methods, longitudinal data analysis, statistical modelling, analysis of dental data, interval;

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Survival Analysis with Interval-Censored Data

include Bayesian methods, longitudinal data analysis, statistical modelling, analysis of dental data, interval-censored data, misclassification;

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Bayesian Modeling in Bioinformatics

Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high;

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Bayesian Modeling in Bioinformatics

Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high;

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Bayesian Compendium

This book describes how Bayesian methods work. Its primary aim is to demystify them, and to show readers: Bayesian thinking isn't difficult;

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Bayesian Compendium

This book describes how Bayesian methods work. Its primary aim is to demystify them, and to show readers: Bayesian thinking isn't difficult;

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Bayesian Networks An Introduction

Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic;

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Bayesian Analysis with R for Drug Development

Sciences at AstraZeneca. He has extensively contributed statistical methods to the biopharmaceutical literature. Novick is a skilled Bayesian;

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Bayesian Analysis with R for Drug Development

Sciences at AstraZeneca. He has extensively contributed statistical methods to the biopharmaceutical literature. Novick is a skilled Bayesian;

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Bayesian Model Selection and Statistical Modeling

Along with many practical applications, Bayesian Model Selection and Statistical Modeling presents an array of Bayesian inference and model;

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Bayesian Approaches in Oncology Using R and OpenBUGS

foundation for later chapters. Many books on the bayesian approach and the statistical analysis are advanced, and many are theoretical. While most;

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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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