TY - BOOK ID - 49885715 TI - Spatial regression analysis using eigenvector spatial filtering AU - Griffith, Daniel AU - Chun, Yongwan AU - Arbia, Giuseppe AU - Legendre, Pierre AU - Li, Bin PY - 2019 SN - 0128156929 0128150432 9780128156926 9780128150436 PB - London, England : Academic Press, DB - UniCat KW - Spatial analysis (Statistics) KW - Regression analysis. KW - Eigenvectors. KW - Matrices KW - Vector spaces KW - Eigenfactor KW - Analysis, Regression KW - Linear regression KW - Regression modeling KW - Multivariate analysis KW - Structural equation modeling KW - Analysis, Spatial (Statistics) KW - Correlation (Statistics) KW - Spatial systems UR - https://www.unicat.be/uniCat?func=search&query=sysid:49885715 AB - "Spatial Regression Analysis Using Eigenvector Spatial Filtering provides both theoretical foundations and guidance on practical implementation for the eigenvector spatial filtering (ESF) technique. ESF is a novel and powerful spatial statistical methodology that allows spatial scientists to account for spatial autocorrelation in georeferenced data analyses. With its flexible structure, ESF can be easily applied to generalized linear regression models. The book discusses ESF specifications for various intermediate-level topics, including spatially varying coefficients models, (non) linear mixed models, local spatial autocorrelation, and spatial interaction models. In addition, it provides a tutorial for ESF model specification and interfaces, including author developed, user-friendly software"-- ER -