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Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Publicado por Taylor & Francis Ltd, London, 2019
ISBN 10: 1138732354 ISBN 13: 9781138732353
Idioma: Inglés
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Añadir al carritoHardcover. Condición: new. Hardcover. 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. State-of-the-art methods in model-based geostatistics (MBG) and its application to problems in global public health. Scientific objective is to describe the pattern of spatial variation in a health outcome using explicit probability models and established principles of statistical inference. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Añadir al carritoCondición: Poor. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In poor condition, suitable as a reading copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,550grams, ISBN:9780387329079.
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Publicado por Taylor & Francis Group, 2019
ISBN 10: 1138732354 ISBN 13: 9781138732353
Idioma: Inglés
Librería: Majestic Books, Hounslow, Reino Unido
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Publicado por Taylor & Francis Group, 2019
ISBN 10: 1138732354 ISBN 13: 9781138732353
Idioma: Inglés
Librería: Books Puddle, New York, NY, Estados Unidos de America
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Añadir al carritoCondición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,500grams, ISBN:9781441921932.
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
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Añadir al carritoHardback. Condición: New. New copy - Usually dispatched within 4 working days.
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Añadir al carritoHardcover. Condición: Brand New. 247 pages. 9.25x6.25x0.75 inches. In Stock.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Publicado por Taylor & Francis Group, 2019
ISBN 10: 1138732354 ISBN 13: 9781138732353
Idioma: Inglés
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 137,27
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Publicado por Taylor & Francis Ltd, London, 2019
ISBN 10: 1138732354 ISBN 13: 9781138732353
Idioma: Inglés
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 121,24
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Añadir al carritoHardcover. Condición: new. Hardcover. 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. State-of-the-art methods in model-based geostatistics (MBG) and its application to problems in global public health. Scientific objective is to describe the pattern of spatial variation in a health outcome using explicit probability models and established principles of statistical inference. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
EUR 113,60
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Añadir al carritoGebunden. Condición: 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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Añadir al carritoCondición: New. pp. 246.
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Librería: BennettBooksLtd, San Diego, NV, Estados Unidos de America
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Añadir al carritohardcover. Condición: New. In shrink wrap. Looks like an interesting title!