Shu Kay Ng, Liming Xiang, Kelvin Kai Wing Yau

Mixture Modelling for Medical and Health Sciences (eBook, ePUB)

• Format: ePub

Produktbeschreibung

Mixture Modelling for Medical and Health Sciences provides a direct connection between theoretical developments in mixture modelling and their applications in real world problems. The book describes the development of the most important concepts through comprehensive analyses of real and practical examples taken from real-life research problems in

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 300
• Erscheinungstermin: 3. Mai 2019
• Englisch
• ISBN-13: 9780429529092
• Artikelnr.: 56679677

Autorenporträt

Dr Angus Ng is a Professor of Biostatistics in the School of Medicine, Griffith University. He was awarded his PhD degree in statistics from the University of Queensland in 1999. Dr Ng is an experienced researcher, with expertise in the fields of biostatistics, statistical modelling, cluster analysis, pattern recognition, machine learning, image analysis, and survival analysis. In these areas, he has more than 100 publications. The focus in the field of statistical modelling has been on the theory and applications of finite mixture models and on estimation via the EM algorithm. In his pioneering work on mixture model-based clustering of longitudinal data, he has elucidated a clear vision for the role of random-effects models to provide a sound theoretical framework for classifying correlated longitudinal data and exploring possible relationships among groups of correlated subjects.

Dr Ng was awarded six ARC grants and has been actively involved in multidisciplinary research projects, NHMRC research projects, as well as consultancy and Government contracts. He is also a researcher with the Centre for Applied Health Economics (CAHE) and is an Associate Editor of the Journal of Statistical Computation and Simulation.

Prof. Kelvin K W Yau is a professor in the department of management sciences at the City University of Hong Kong. His research interests include Generalized Linear Mixed Models, Multivariate Survival Analysis, Finite Mixture Models, Robust Estimation, Statistical Modelling and Zero-Inflated-Poisson Models.

Liming Xiang is a professor of statistics at Nanyang Technological University in Singapore. She got her PhD degree in 2002 from the City University of Hong Kong. She serves as associate editor for Statistics in Medicine, Computational Statistics & Data Analysis and Journal of Statistical Computation and Simulation.