This book will be the first to present the foundational issues of Bayesian modeling, finite and infinite mixture models, and MCMC computational methods, together with a range of detailed case studies covering the applications of the methods. The applications are drawn from a wide range of scientific disciplines, including biostatistics, ecology, bioinformatics, the social sciences and finance.

Bayesian Analysis of Mixtures: Foundations and Applications (Wiley Series in Probability and Statistics)

Science & Math

Mengersen, Kerrie L.

Mathematics

wiley

Hospitals monitoring is becoming more complex and is increasing both because staff want their data analysed and because of increasing mandated surveillance. This book provides a suite of functions in R, enabling scientists and data analysts working in infection management and quality improvement departments in hospitals, to analyse their often non-independent data which is frequently in the form of trended, over-dispersed and sometimes auto-correlated time series; this is often difficult to analyse using standard office software. This book provides much-needed guidance on data analysis using R for the growing number of scientists in hospital departments who are responsible for producing reports, and who may have limited statistical expertise. This book explores data analysis using R and is aimed at scientists in hospital departments who are responsible for producing reports, and who are involved in improving safety. Professionals working in the healthcare quality and safety community will also find this book of interest Statistical Methods for Hospital Monitoring with R: <ul>
<li>Provides functions to perform quality improvement and infection management data analysis.</li> <li>Explores the characteristics of complex systems, such as self-organisation and emergent behaviour, along with their implications for such activities as root-cause analysis and the Pareto principle that seek few key causes of adverse events.</li> <li>Provides a summary of key non-statistical aspects of hospital safety and easy to use functions.</li> <li>Provides R scripts in an accompanying web site enabling analyses to be performed by the reader http://www.wiley.com/go/hospital_monitoring</li> <li>Covers issues that will be of increasing importance in the future, such as, generalised additive models, and complex systems, networks and power laws.</li> </ul>

Statistical Methods for Hospital Monitoring with R

Medical Books

Whitby, Michael

Morton, Anthony

Playford, Geoffrey

Administration & Medicine Economics

This book uses the EM (expectation maximization) algorithm to simultaneously estimate the missing data and unknown parameter(s) associated with a data set. The parameters describe the component distributions of the mixture; the distributions may be continuous or discrete. 
The editors provide a complete account of the applications, mathematical structure and statistical analysis of finite mixture distributions along with MCMC computational methods, together with a range of detailed discussions covering the applications of the methods and features chapters from the leading experts on the subject. The applications are drawn from scientific discipline, including biostatistics, computer science, ecology and finance. This area of statistics is important to a range of disciplines, and its methodology attracts interest from researchers in the fields in which it can be applied.

Mixtures: Estimation and Applications

Robert, Christian

Titterington, Mike

Biological Sciences

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Books by Mengersen, Kerrie L.