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πŸ“

Hierarchical Modeling and Analysis for Spatial Data

✍ Scribed by Banerjee, Sudipto; Carlin, Bradley P.; Gelfand, Alan E


Publisher
Chapman & Hall/CRC
Year
2003
Tongue
English
Leaves
583
Series
Chapman & Hall/CRC Monographs on Statistics & Applied Probability
Category
Library

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✦ Table of Contents


Content: Overview of spatial data problems --
Basics of point-referenced data models --
Basics of areal data models --
Basics of Bayesian inference --
Hierarchical modeling for univariate spatial data --
Spatial misalignment --
Multivariate spatial modeling --
Spatiotemporal modeling --
Spatial survival models --
Special topics in spatial process modeling

✦ Subjects


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πŸ“œ SIMILAR VOLUMES


Hierarchical Modeling and Analysis for S
✍ Sudipto Banerjee, Bradley P. Carlin, Alan E. Gelfand πŸ“‚ Library πŸ“… 2003 πŸ› Chapman and Hall\/CRC 🌐 English

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 narrowl

Hierarchical Modeling and Analysis for S
✍ Banerjee, Sudipto; Carlin, Bradley P.; Gelfand, Alan E πŸ“‚ Library πŸ“… 2015 πŸ› CRC Press 🌐 English

""This is a very welcome second edition of a nice and very successful book written by three experts in the field ... I have no doubts that this updated text will continue being a compulsory reference for those graduate students and researchers interested in understanding and applying any of the thre

Data Analysis Using Regression and Multi
✍ Andrew Gelman, Jennifer Hill πŸ“‚ Library πŸ“… 2007 πŸ› Cambridge University Press 🌐 English

I got this book while working on an article that involved a hierarchical model with a binary dependent variable - after poking through Radenbush/Bryk and a variety of other texts that left me frustrated. Not only did this book teach me how to properly specify and estimate the model in R, I also lear

Data Analysis Using Regression and Multi
✍ Andrew Gelman; Jennifer Hill πŸ“‚ Library πŸ“… 2006 πŸ› Cambridge University Press 🌐 English

John Fox introduces readers to the techniques of kernel estimation, additive nonparametric regression, and the ways nonparametric regression can be employed to select transformations of the data preceding a linear least-squares fit "Data Analysis Using Regression and Multilevel/Hierarchical Models

Data Analysis Using Regression and Multi
✍ Andrew Gelman, Jennifer Hill πŸ“‚ Library πŸ“… 2006 πŸ› Cambridge University Press 🌐 English

Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the