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Model-based Geostatistics for Global Public Health (Chapman & Hall/CRC Interdisciplinary Statistics)
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Model-based Geostatistics for Global Public Health (Chapman & Hall/CRC Interdisciplinary Statistics)
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Model-based Geostatistics for Global Public Health (Chapman & Hall/CRC Interdisciplinary Statistics)
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Model-based Geostatistics for Global Public Health (Chapman & Hall/CRC Interdisciplinary Statistics)
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Model-based Geostatistics for Global Public Health: Methods and Applications (Chapman & Hall/CRC Interdisciplinary Statistics)
Published by Routledge 2021-06-30, 2021
ISBN 10: 1032093641 ISBN 13: 9781032093642
Language: English
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Model-based Geostatistics for Global Public Health
Published by Taylor & Francis Group, 2019
ISBN 10: 1138732354 ISBN 13: 9781138732353
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Model-based Geostatistics for Global Public Health
Published by Taylor & Francis Group, 2019
ISBN 10: 1138732354 ISBN 13: 9781138732353
Language: English
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Model-based Geostatistics for Global Public Health: Methods and Applications
Published by Taylor & Francis Ltd, 2019
ISBN 10: 1138732354 ISBN 13: 9781138732353
Language: English
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Model-based Geostatistics for Global Public Health
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ISBN 10: 1138732354 ISBN 13: 9781138732353
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Add to basketGebunden. Condition: New. Model-based Geostatistics for Global Public Health: Methods and Applications provides an introductory account of model-based geostatistics, its implementation in open-source software and its application in public health research. In the .
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Model-based Geostatistics for Global Public Health : Methods and Applications
Published by Taylor & Francis Ltd Mär 2019, 2019
ISBN 10: 1138732354 ISBN 13: 9781138732353
Language: English
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Model-based Geostatistics for Global Public Health
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Model-based Geostatistics for Global Public Health: Methods and Applications provides an introductory account of model-based geostatistics, its implementation in open-source software and its application in public health research. In the .
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Model-based Geostatistics for Global Public Health : Methods and Applications
Published by Chapman And Hall/CRC, 2021
ISBN 10: 1032093641 ISBN 13: 9781032093642
Language: English
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Model-based Geostatistics for Global Public Health: Methods and Applications provides an introductory account of model-based geostatistics, its implementation in open-source software and its application in public health research. In the public health problems that are the focus of this book, the authors describe and explain the pattern of spatial variation in a health outcome or exposure measurement of interest. Model-based geostatistics uses explicit probability models and established principles of statistical inference to address questions of this kind.Features:Presents state-of-the-art methods in model-based geostatistics.Discusses the application these methods some of the most challenging global public health problems including disease mapping, exposure mapping and environmental epidemiology.Describes exploratory methods for analysing geostatistical data, including: diagnostic checking of residuals standard linear and generalized linear models; variogram analysis; Gaussian process models and geostatistical design issues.Includes a range of more complex geostatistical problems where research is ongoing.All of the results in the book are reproducible using publicly available R code and data-sets, as well as a dedicated R package.This book has been written to be accessible not only to statisticians but also to students and researchers in the public health sciences.The AuthorsPeter Diggle is Distinguished University Professor of Statistics in the Faculty of Health and Medicine, Lancaster University. He also holds honorary positions at the Johns Hopkins University School of Public Health, Columbia University International Research Institute for Climate and Society, and Yale University School of Public Health. His research involves the development of statistical methods for analyzing spatial and longitudinal data and their applications in the biomedical and health sciences.Dr Emanuele Giorgi is a Lecturer in Biostatistics and member of the CHICAS research group at Lancaster University, where he formerly obtained a PhD in Statistics and Epidemiology¿in 2015. His research interests involve the development of novel geostatistical methods for disease mapping, with a special focus on malaria and other tropical diseases. In 2018, Dr Giorgi was awarded the Royal Statistical Society Research Prize 'for outstanding published contribution at the interface of statistics and epidemiology.' He is also the lead developer of PrevMap, an R package where all the methodology found in this book has been implemented.
