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in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: * Illustrates how to do Bayesian analysis;
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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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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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These lecture notes provide a rapid, accessible introduction to Bayesian statistical methods. The course covers the fundamental philosophy;
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in statistics and data analysis. This second edition is extensively revised, especially those sections relating with Bayesian concepts.;
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assume relatively little previous statistical or mathematical knowledge. Introducing the idea underlying the Bayesian approach to the statistical;
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collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian;
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collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian;
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programs.Bayesian Statistical Modelling is ideal for researchers in applied statistics, medical science, public health and the social;
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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, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility;
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This volume describes how to develop Bayesian thinking, modelling and computation both from philosophical, methodological and application;
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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 Modeling is a step-by-step guide to the Bayesian revolution in regression modeling, for use in advanced;
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Leuven. His research interests include Bayesian methods, longitudinal data analysis, statistical modelling, analysis of dental data, interval;
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include Bayesian methods, longitudinal data analysis, statistical modelling, analysis of dental data, interval-censored data, misclassification;
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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 discusses the development and application of Bayesian statistical methods for the analysis of high;
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This book describes how Bayesian methods work. Its primary aim is to demystify them, and to show readers: Bayesian thinking isn't difficult;
Vergelijkbare producten zoals 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;
Vergelijkbare producten zoals Bayesian Compendium
Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic;
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Sciences at AstraZeneca. He has extensively contributed statistical methods to the biopharmaceutical literature. Novick is a skilled Bayesian;
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Sciences at AstraZeneca. He has extensively contributed statistical methods to the biopharmaceutical literature. Novick is a skilled Bayesian;
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Along with many practical applications, Bayesian Model Selection and Statistical Modeling presents an array of Bayesian inference and model;
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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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Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian;
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Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian;
Vergelijkbare producten zoals Statistical Inference
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