Hierarchical Modeling and Analysis for Spatial Data

Hierarchical Modeling and Analysis for Spatial Data
Author: Sudipto Banerjee
Publisher: CRC Press
Total Pages: 470
Release: 2003-12-17
Genre: Mathematics
ISBN: 1135438080


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Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis,


Hierarchical Modeling and Analysis for Spatial Data
Language: en
Pages: 470
Authors: Sudipto Banerjee
Categories: Mathematics
Type: BOOK - Published: 2003-12-17 - Publisher: CRC Press

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Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology
Hierarchical Modeling and Analysis for Spatial Data, Second Edition
Language: en
Pages: 587
Authors: Sudipto Banerjee
Categories: Mathematics
Type: BOOK - Published: 2014-09-12 - Publisher: CRC Press

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Keep Up to Date with the Evolving Landscape of Space and Space-Time Data Analysis and Modeling Since the publication of the first edition, the statistical lands
Hierarchical Modeling and Inference in Ecology
Language: en
Pages: 463
Authors: J. Andrew Royle
Categories: Science
Type: BOOK - Published: 2008-10-15 - Publisher: Elsevier

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A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a
Hierarchical Modeling and Analysis for Spatial Data
Language: en
Pages: 470
Authors: Sudipto Banerjee
Categories: Mathematics
Type: BOOK - Published: 2003-12-17 - Publisher: CRC Press

GET EBOOK

Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology
Data Analysis Using Regression and Multilevel/Hierarchical Models
Language: en
Pages: 654
Authors: Andrew Gelman
Categories: Mathematics
Type: BOOK - Published: 2007 - Publisher: Cambridge University Press

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This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.