Shu kay (37 risultati)

paperback. Condizione: Like New. Most items will be dispatched the same or the next working day. An apparently unread copy in perfect condition. Dust cover is intact with no nicks or tears. Spine has no signs of creasing. Pages are clean and not marred by notes or folds of any kind.

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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.

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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

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Paperback. Condizione: Brand New. 314 pages. 9.21x6.14x1.22 inches. In Stock.

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Hardcover. Condizione: new. Hardcover. 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. This approach represents balance between "theory" and "practice", stimulating readers and enhancing their capacity to apply mixture models in data analysis. Full of reproducible examples using software code and publicly-available data, the book is suitable for graduate-level students, researchers, and practitioners who have a basic grounding in statistics and would like to explore the use of mixture models to analyse their experiments and research data.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. Focuses on full analyses of real data sets based on the needs and requirements of end users. Fundamental theory is introduced with emphasis on the motivation by challenges coming from real problems with real data. Complete explanations of important concepts are provided, but the amount of mathematical derivation of formulation is minimized. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Condizione: New. 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 .

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Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.

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paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

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Hardcover. Condizione: Brand New. 302 pages. 9.50x6.50x1.00 inches. In Stock.

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Condizione: New. In English.

Taschenbuch. Condizione: Neu. Neuware - 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. This approach represents balance between 'theory' and 'practice', stimulating readers and enhancing their capacity to apply mixture models in data analysis. Full of reproducible examples using software code and publicly-available data, the book is suitable for graduate-level students, researchers, and practitioners who have a basic grounding in statistics and would like to explore the use of mixture models to analyse their experiments and research data.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.…