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Circular Data Bayesian Modeling

of the phenomena under study. But these improvements have not concerned in the same way the statistical modeling of circular data (i.e. data;

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Introduction to Hierarchical Bayesian Modeling for Ecological Data

. Data sets, exercises, and R and WinBUGS codes are available on the authors' website. This book shows how Bayesian statistical modeling;

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Introduction to Hierarchical Bayesian Modeling for Ecological Data

. Data sets, exercises, and R and WinBUGS codes are available on the authors' website. This book shows how Bayesian statistical modeling;

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Bayesian Disease Mapping

Focusing on data commonly found in public health databases and clinical settings, Bayesian Disease Mapping: Hierarchical Modeling;

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Bayesian Modeling in Bioinformatics

error and survival models for cDNA microarrays, a Bayesian hidden Markov modeling approach for CGH array data, Bayesian approaches for;

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Bayesian Modeling in Bioinformatics

error and survival models for cDNA microarrays, a Bayesian hidden Markov modeling approach for CGH array data, Bayesian approaches for;

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Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

in applying Bayesian methodology in small area health data studies. Features: Review of R graphics relevant to spatial health data;

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Essential Bayesian Models

This accessible reference includes selected contributions from Bayesian Thinking - Modeling and Computation, Volume 25 in the Handbook;

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Bayesian Item Response Modeling

motives for writing this book is to give an introduction to the Bayesian methodology for modeling and analyzing item response data. A Bayesian;

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Bayesian Methods For Data Analysis

Broadening its scope to nonstatisticians, Bayesian Methods for Data Analysis, Third Edition provides an accessible introduction to the;

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Bayesian Disease Mapping

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the;

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Bayesian Disease Mapping

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the;

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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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Bayesian Analysis with Python

data analyses using PyMC3 and ArviZ A modern, practical and computational approach to Bayesian statistical modeling A tutorial for Bayesian;

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Bayesian Statistics for the Social Sciences

practical skills they need to apply Bayesian methodologies to their data analysis problems. Part I addresses the elements of Bayesian inference;

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Bayesian Data Analysis

is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research;

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Bayesian Ideas And Data Analysis

Emphasizing the use of WinBUGS and R to analyze real data, Bayesian Ideas and Data Analysis: An Introduction for Scientists and;

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Bayesian Artificial Intelligence

of Bayesian network technology, automated causal discovery, and learning probabilities from data and shows how to employ these technologies to develop;

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Bayesian Artificial Intelligence

presents the elements of Bayesian network technology, automated causal discovery, and learning probabilities from data and shows how to employ;

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Bayesian Analysis in Natural Language Processing

data-driven techniques to analyze language.Since then, the use of statistical techniques in NLP has evolved in several ways. One such example;

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Bayesian Cognitive Modeling

this book, readers should be able to build their own Bayesian models, apply the models to their own data, and draw their own conclusions.;

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Bayesian Cognitive Modeling

this book, readers should be able to build their own Bayesian models, apply the models to their own data, and draw their own conclusions.;

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Bayesian Models for Astrophysical Data

This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to;

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Bayesian Model Comparison

issues include parallel computation, Hamiltonian Monte Carlo, dynamic model selection, small sample comparison of structural models, Bayesian;

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Bayesian and grAphical Models for Biomedical Imaging

This book constitutes the refereed proceedings of the First International Workshop on Bayesian and grAphical Models for Biomedical Imaging;

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Missing Data in Longitudinal Studies

Bayesian Modeling and Sensitivity Analysis describes a comprehensive Bayesian approach for drawing inference from incomplete data in longitudinal;

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Models for Ecological Data

from classical to Bayesian methods. Through an available lab manual, the book introduces readers to the practical work of data modeling and;

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