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An Introduction to Bayesian Inference and Decision

An Introduction to Bayesian Inference and Decision is een boek van Robert L Winkler;

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An Introduction to Bayesian Inference in Econometrics

volume is an early introduction to Bayesian inference and methodology which still has lasting value for today's statistician and student. The;

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Introduction to Statistical Decision Theory

Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to approach decision;

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Introduction to Statistical Decision Theory

Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to approach decision;

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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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Bayesian Analysis of Stochastic Process Models

, computational, inference, forecasting, decision making and important applied models. Key features: * Explores Bayesian analysis of models based on;

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Bayesian Programming

financial investments to email filtering, are incomplete or uncertain in nature. Probability theory and Bayesian computing together provide an;

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Bayesian Programming

financial investments to email filtering, are incomplete or uncertain in nature. Probability theory and Bayesian computing together provide an;

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Bayesian Modeling Using WinBUGS

A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using WinBUGS provides an easily accessible;

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Introduction to Bayesian Statistics

with chapter exercises. Introduction to Bayesian Statistics, Third Edition also features: * Topics including the Joint Likelihood function and;

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Statistical Inference

solutions to difficult model comparison problems and offers direct Bayesian counterparts of frequentist t-tests and other standard statistical;

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Statistical Inference

solutions to difficult model comparison problems and offers direct Bayesian counterparts of frequentist t-tests and other standard statistical;

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Probability and Bayesian Modeling

Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus;

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Bayesian Inference

This text is written to provide a mathematically sound but accessible and engaging introduction to Bayesian inference specifically for;

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Bayesian Inference for Probabilistic Risk Assessment

perform or review risk analyses. It provides an analytical structure for combining data and information from various sources to generate estimates;

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Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists

of these issues. Subsequent chapter coverage features:* An introduction to the fundamental concepts of Bayesian statistical analysis, including;

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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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Modeling and Reasoning with Bayesian Networks

This book is a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive;

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Modeling and Reasoning with Bayesian Networks

This book is a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive;

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Bayesian Logical Data Analysis for the Physical Sciences

problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model;

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Bayesian Logical Data Analysis for the Physical Sciences

problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model;

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Modeling in Medical Decision Making

decision making. Provides an overview of the necessary methodological background, including Bayesian inference, Monte Carlo simulation, and;

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Probabilistic Graphical Models

This accessible text/reference provides a general introduction to probabilistic graphical models (PGMs) from an engineering perspective;

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Bayesian Networks and Decision Graphs

This is a brand new edition of an essential work on Bayesian networks and decision graphs. It is an introduction to probabilistic graphical;

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The Bayesian Choice

This is an introduction to Bayesian statistics and decision theory, including advanced topics such as Monte Carlo methods. This new edition;

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Bayesian Methods For Hackers

algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to;

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Likelihood and Bayesian Inference

likelihood ratio and the Wald statistic. In the second part of the book, likelihood is combined with prior information to perform Bayesian inference;

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