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Understanding the Tripartite Approach to Bayesian Divergence Time Estimation

describe the tripartite model used for Bayesian estimation of time calibrated phylogenetic trees. The model can be readily separated into its;

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Bayesian Phylogenetics

interdisciplinary research, this book introduces state-of-the-art phylogenetics to the Bayesian statistical community and, likewise, presents state-of-the;

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Bayesian Estimation and Tracking

nonlinear dynamic systems driven by Gaussian and non-Gaussian noices. Featuring a unified approach to Bayesian estimation and tracking, the book;

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Bayesian Inference for Stochastic Processes

(estimation, testing hypotheses, and prediction) for the unknown parameters of stochastic processes To illustrate the Bayesian;

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Bayesian Inference for Stochastic Processes

disciplines. In order analyses of stochastic processes, it will use R and WinBUGS. Features: Uses the Bayesian approach to make;

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Economic Forecasting

financial risk to predicting inflation and stock market returns. Economic Forecasting presents a comprehensive, unified approach to assessing the;

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Bayesian Methods for Measures of Agreement

. The author employs a Bayesian approach to provide statistical inferences based on various models of intra- and interrater agreement. He;

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Bayesian Methods for Measures of Agreement

. The author employs a Bayesian approach to provide statistical inferences based on various models of intra- and interrater agreement. He;

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Introduction to Bayesian Estimation and Copula Models of Dependence

Introduction to Bayesian Estimation and Copula Models of Dependence emphasizes the applications of Bayesian analysis to copula modeling and equips;

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Inside Volatility Filtering

A new, more accurate take on the classical approach to volatility evaluation Inside Volatility Filtering presents a new approach to;

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Bayesian Analysis of Time Series

models that explain the probabilistic characteristics of these time series and then utilizes the Bayesian approach to make inferences about their;

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Bayesian Analysis of Time Series

models that explain the probabilistic characteristics of these time series and then utilizes the Bayesian approach to make inferences about their;

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Bayesian Psychometric Modeling

Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to conventional;

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Bayesian Psychometric Modeling

unified Bayesian approach across traditionally separate families of psychometric models. It shows that Bayesian techniques, as alternatives to;

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Multivariate Bayesian Statistics: Models for Source Separation and Signal Unmixing

not only allow estimation of the sources and mixing coefficients, but also allow inferences to be drawn from them. Multivariate Bayesian;

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Modeling and Estimation of Structural Damage

Modelling and Estimation of Damage in Structures is a comprehensiveguide to solving the type of modelling and estimation problems;

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Bayesian Demographic Estimation and Forecasting

Bayesian Demographic Estimation and Forecasting presents three statistical frameworks for modern demographic estimation and forecasting;

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Bayesian Demographic Estimation and Forecasting

Bayesian Demographic Estimation and Forecasting presents three statistical frameworks for modern demographic estimation and forecasting;

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Bayesian Methods in Epidemiology

regression, and nonlinear models. The text also introduces a Bayesian approach for the estimation of survival by life tables and illustrates other;

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Bayesian Methods in Epidemiology

/ordinal regression, and nonlinear models. The text also introduces a Bayesian approach for the estimation of survival by life tables and;

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Particle Filters for Random Set Models

Bayesian estimation in the framework of random set theory have provided new opportunities which are not widely known and are covered in this book;

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Bayesian Cognitive Modeling

and cognitive science, however, have failed to take full advantage of the new and exciting possibilities that the Bayesian approach affords;

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Bayesian Cognitive Modeling

and cognitive science, however, have failed to take full advantage of the new and exciting possibilities that the Bayesian approach affords;

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Unit Roots, Cointegration, and Structural Change

also present the Bayesian approach to these problems and bootstrap methods for small-sample inference. The chapters on structural change;

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Bayesian Analysis of Linear Models

methods of estimation, hypothesis,testing, and forecasting as applied to the standard populations ... somethinginnovative-a new approach to mixed;

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Bayesian Analysis of Linear Models

methods of estimation, hypothesis,testing, and forecasting as applied to the standard populations ... somethinginnovative-a new approach to mixed;

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Think Bayes

out of the way, the Bayesian fundamentals will become clearer and you'll begin to apply these techniques to real-world problems. Bayesian;

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