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Model-based Geostatistics for Global Public Health: Methods and Applications

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Model-based Geostatistics for Global Public Health: Methods and Applications. / Diggle, Peter John; Giorgi, Emanuele.
London: CRC Press, 2019. 248 p. (Chapman & Hall/CRC Interdisciplinary Statistics).

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Diggle PJ, Giorgi E. Model-based Geostatistics for Global Public Health: Methods and Applications. London: CRC Press, 2019. 248 p. (Chapman & Hall/CRC Interdisciplinary Statistics).

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Diggle, Peter John ; Giorgi, Emanuele. / Model-based Geostatistics for Global Public Health : Methods and Applications. London : CRC Press, 2019. 248 p. (Chapman & Hall/CRC Interdisciplinary Statistics).

Bibtex

@book{f5bb216103b440c79a9dca465cb36557,
title = "Model-based Geostatistics for Global Public Health: Methods and Applications",
abstract = "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.",
author = "Diggle, {Peter John} and Emanuele Giorgi",
year = "2019",
month = mar,
day = "13",
language = "English",
isbn = "9781138732353",
series = "Chapman & Hall/CRC Interdisciplinary Statistics",
publisher = "CRC Press",

}

RIS

TY - BOOK

T1 - Model-based Geostatistics for Global Public Health

T2 - Methods and Applications

AU - Diggle, Peter John

AU - Giorgi, Emanuele

PY - 2019/3/13

Y1 - 2019/3/13

N2 - 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.

AB - 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.

M3 - Book

SN - 9781138732353

T3 - Chapman & Hall/CRC Interdisciplinary Statistics

BT - Model-based Geostatistics for Global Public Health

PB - CRC Press

CY - London

ER -