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Bayesian Multivariate Time Series Methods for Empirical Macroeconomics

Bayesian Multivariate Time Series Methods for Empirical Macroeconomics provides a survey of the Bayesian methods used in modern empirical;

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Bayesian Time Series Models

'What's going to happen next?' Time series data hold the answers, and Bayesian methods represent the cutting edge in learning what they;

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Time Series

Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and;

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Time Series

Focusing on Bayesian approaches and computations using analytic and simulation-based methods for inference, Time Series: Modeling;

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Bayesian Forecasting and Dynamic Models

of classes of dynamic models and their uses in forecasting and time series analysis. The principles, models and methods of Bayesian forecasting and;

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Bayesian Models for Categorical Data

The use of Bayesian methods for the analysis of data has grown substantially in areas as diverse as applied statistics, psychology;

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Asymptotics, Nonparametrics, and Time Series

Contains over 2500 equations and exhaustively covers not only nonparametrics but also parametric, semiparametric, frequentist, Bayesian;

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Bayesian Econometric Methods

Bayesian Econometric Methods examines principles of Bayesian inference by posing a series of theoretical and applied questions and;

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Bayesian Econometric Methods

Bayesian Econometric Methods examines principles of Bayesian inference by posing a series of theoretical and applied questions and;

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Asymptotics, Nonparametrics, and Time Series

"Contains over 2500 equations and exhaustively covers not only nonparametrics but also parametric, semiparametric, frequentist, Bayesian;

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Bayesian Analysis of Time Series

In many branches of science relevant observations are taken sequentially over time. Bayesian Analysis of Time Series discusses how to use;

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Bayesian Analysis of Time Series

In many branches of science relevant observations are taken sequentially over time. Bayesian Analysis of Time Series discusses how to use;

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Bringing Bayesian Models to Life

Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental;

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Bringing Bayesian Models to Life

Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental;

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Handbook of Discrete-Valued Time Series

series of counts and incorporates frequentist and Bayesian approaches for discrete-valued spatio-temporal data and multivariate data. While the;

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Handbook of Discrete-Valued Time Series

series of counts and incorporates frequentist and Bayesian approaches for discrete-valued spatio-temporal data and multivariate data. While the;

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Applied Bayesian Forecasting and Time Series Analysis

Practical in its approach, Applied Bayesian Forecasting and Time Series Analysis provides the theories, methods, and tools necessary for;

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Applied Bayesian Forecasting and Time Series Analysis

Practical in its approach, Applied Bayesian Forecasting and Time Series Analysis provides the theories, methods, and tools necessary for;

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Bayesian Modeling and Computation in Python

models including linear regressions, splines, time series, Bayesian additive regression trees. The final chapters include Approximate Bayesian;

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Essential Bayesian Models

of Statistics Series, with a focus on key methodologies and applications for Bayesian models and computation. It describes parametric and nonparametric;

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A Course in Time Series Analysis

series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes;

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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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The Structural Econometric Time Series Analysis Approach

relations between dynamic econometric structural models and empirical time series MVARMA, VAR, transfer function, and univariate ARIMA models are;

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The Structural Econometric Time Series Analysis Approach

relations between dynamic econometric structural models and empirical time series MVARMA, VAR, transfer function, and univariate ARIMA models are;

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Interrupted Time Series Analysis

Interrupted Time Series Analysis develops a comprehensive set of models and methods for drawing causal inferences from time series. It;

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Likelihood & 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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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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