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Hierarchical Modeling and Analysis for Spatial Data (Chapman & Hall/CRC Monographs on Statistics & Applied Probability) by Sudipto Banerjee; Bradley P. Carlin; Alan E. Gelfand; Sudipto Banerjee is a nonfiction available to read on EtoBox.
What is Hierarchical Modeling and Analysis for Spatial Data (Chapman & Hall/CRC Monographs on Statistics & Applied Probability) about?
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, or written at a level often inaccessible to those lacking a strong background in mathematical statistics. Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and data analysis for spatial and spatio-temporal data. Starting with overviews of the types of spatial data, the data analysis tools appropriate for each, and a brief review of the Bayesian approach to statistics, the authors discuss hierarchical modeling for univariate spatial response data, including Bayesian kriging and lattice (areal data) modeling. They then consider the problem of spatially misaligned data, methods for handling multivariate spatial responses, spatio-temporal models, and spatial survival models. The final chapter explores a variety of special topics, including spatially varyin
Who reads Hierarchical Modeling and Analysis for Spatial Data (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Sudipto Banerjee; Bradley P. Carlin; Alan E. Gelfand; Sudipto Banerjee
- Publisher
- Chapman and Hall/CRC
- Published
- 2003
- Language
- EN
- ISBN
- 9781135438074
- Category
- nonfiction
- Subjects
- Mathematics, Computer Science, Technology
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