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Bayesian Analysis of Gene Expression Data

exclusively to Bayesian methods of analysis for applications to high-throughput gene expression data, exploring the relevant methods that are changing;

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Bayesian Modeling in Bioinformatics

phylogenic analysis, sparsity priors for protein-protein interaction predictions, and Bayesian networks for gene expression data. The text also;

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Bayesian Modeling in Bioinformatics

phylogenic analysis, sparsity priors for protein-protein interaction predictions, and Bayesian networks for gene expression data. The text also;

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Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods;

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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 Approaches in Oncology Using R and OpenBUGS

statistical application framework: Bayesian in Clinical Research and Sample Size Calcuation Bayesian in Time-to-Event Data Analysis;

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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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Bayesian Analysis with Python

Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ Key Features A step-by-step guide to conduct Bayesian;

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Bayesian Data Analysis

problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors;

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Bayesian Analysis with Python

Students, researchers and data scientists who wish to learn Bayesian data analysis with Python and implement probabilistic models in their day to;

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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 Analysis Made Simple

focused on practical issues, or generally too difficult to understand. Bayesian Analysis Made Simple is aimed at those who wish to apply;

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Bayesian Analysis Made Simple

focused on practical issues, or generally too difficult to understand. Bayesian Analysis Made Simple is aimed at those who wish to apply;

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Bayesian Decision Analysis

data can be sampled and expert judgements elicited to support this analysis, and when and how an effective Bayesian decision analysis can be;

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Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

professionals alike to engage in the analysis of spatial and spatio-temporal health data from a Bayesian perspective using R. The book emphasizes the;

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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 Statistical Methods

Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis;

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Bayesian Statistical Methods

Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis;

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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 Methods in Health Economics

of Bayesian methods for the analysis of health economic data. After an introduction to the basic economic concepts and methods of evaluation, it;

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Bayesian Methods in Health Economics

of Bayesian methods for the analysis of health economic data. After an introduction to the basic economic concepts and methods of evaluation, it;

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Bayesian Analysis with Stata

Bayesian Analysis with Stata is written for anyone interested in applying Bayesian methods to real data easily. The book shows how modern;

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Bayesian Deconvolution of Sparse Processes

on simulated data. Receiver function analysis, a research topic in seismology, is studied as a real life application. Bayesian deconvolution;

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Bayesian Hierarchical Models

collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian;

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Bayesian Hierarchical Models

collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian;

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Robust Bayesian Analysis

Robust Bayesian analysis aims at overcoming the traditional objection to Bayesian analysis of its dependence on subjective inputs, mainly;

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