Mixture Modelling for Medical and Health Sciences
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"...The examples are rich in diagrams and tables, with explanatory text. The coding parts are less extensive. In any case, such a homogenic structure of the book definitely contributes to increased readability and understandability of quite complex topics. This is especially true in the later chapters, where more advanced methods are discussed...To conclude, this book is a definite asset for those interested in sample clustering and more specifically mixture modelling."
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- Gia Jgarkava, ISCB News, July 2020
"...(This book) by Shu Kay Ng, Liming Xiang and Kelvin Kai Wing Yau connects theoretical modelling to many real-world problems. Noteworthy features of this fascinating book include in-depth up-to-date knowledge on mixture modeling, random effects, among others...The bibliography is exhaustive and complete for the sake of the readers."
- Ramalingam Shanmugam, JSCS, Aug 2020
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 medical and health sciences. Les mer
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Features
An in-depth account of the most up-to-date mixture modelling techniques from auser perspective.
Extensive real-life examples - from typical daily problems to complex data modelling.
Emphasis on the use of a wide variety of component densities for statistical modelling.
Coverage of the latest random-effects models in modelling complex correlated data.
An accompanying website to provide supplementary materials, including software and detailed programming code, and links to available data sources.
Provision of R and Fortran code for readers who want to do analysis of their own data using mixture models.
Shu-Kay Angus Ng is Professor of Biostatistics in the School of Medicine at the Griffith University, Australia. Dr Ng has published extensively on his research interests, which include cluster analysis, pattern recognition, random-effects modelling, and survival analysis.
Liming Xiang is Associate Professor of Statistics in the School of Physical & Mathematical Sciences at the Nanyang Technological University, Singapore. Her research interests include survival analysis, longitudinal/clustered data analysis and mixture models.
Kelvin Kai-wing Yau is Professor of Statistics in the Department of Management Sciences at the City University of Hong Kong. He has been involved in various interdisciplinary research projects, with journal publications in statistics, medical and health science journals on topics such as mixed effects models, survival analysis and statistical modelling in general.
Detaljer
- Forlag
- Chapman & Hall/CRC
- Innbinding
- Innbundet
- Språk
- Engelsk
- Sider
- 302
- ISBN
- 9781482236750
- Utgivelsesår
- 2019
- Format
- 23 x 16 cm
Anmeldelser
«
"...The examples are rich in diagrams and tables, with explanatory text. The coding parts are less extensive. In any case, such a homogenic structure of the book definitely contributes to increased readability and understandability of quite complex topics. This is especially true in the later chapters, where more advanced methods are discussed...To conclude, this book is a definite asset for those interested in sample clustering and more specifically mixture modelling."
»
- Gia Jgarkava, ISCB News, July 2020
"...(This book) by Shu Kay Ng, Liming Xiang and Kelvin Kai Wing Yau connects theoretical modelling to many real-world problems. Noteworthy features of this fascinating book include in-depth up-to-date knowledge on mixture modeling, random effects, among others...The bibliography is exhaustive and complete for the sake of the readers."
- Ramalingam Shanmugam, JSCS, Aug 2020