Spatial Regression Models
2003; Wiley; Linguagem: Italiano
10.1002/0471475769.ch9
ISSN1940-6347
Autores Tópico(s)Regional Economics and Spatial Analysis
ResumoChapter 9 Spatial Regression Models James P. LeSage, James P. LeSageSearch for more papers by this author James P. LeSage, James P. LeSageSearch for more papers by this author Micah Altman, Micah AltmanSearch for more papers by this authorJeff Gill, Jeff GillSearch for more papers by this authorMichael P. McDonald, Michael P. McDonaldSearch for more papers by this author Book Author(s):Micah Altman, Micah AltmanSearch for more papers by this authorJeff Gill, Jeff GillSearch for more papers by this authorMichael P. McDonald, Michael P. McDonaldSearch for more papers by this author First published: 12 December 2003 https://doi.org/10.1002/0471475769.ch9Citations: 5Book Series:Wiley Series in Probability and Statistics Series Editor(s): Walter A. Shewhart, Walter A. ShewhartSearch for more papers by this authorSamuel S. Wilks, Samuel S. WilksSearch for more papers by this author AboutPDFPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShareShare a linkShare onFacebookTwitterLinked InRedditWechat Summary Chapter nine discusses computational issues involved in estimating spatial regression models including: an overview of regression models with spatial dependence maximum likelihood estimation of spatial regression models sparse matrix algorithms for use in estimation of spatial regression trade-offs between speed and accuracy estimation of Bayesian heteroscedastic spatial models using MCMC examples using census data Citing Literature Numerical Issues in Statistical Computing for the Social Scientist RelatedInformation
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