localEM: Nonparametric Modelling of Spatial Risk for Areal Disease Data

Implementing the kernel smoothing local-EM algorithm on disease data aggregated to highly coarse geographical regions while using population data collected on highly fine geographical regions to estimate spatial risk.

AuthorPaul Nguyen, Patrick Brown
Date of publication2016-12-13 20:10:03
MaintainerPaul Nguyen <pablo.nguyen@utoronto.ca>
LicenseGPL-2
Version0.2.0

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Files

localEM/DESCRIPTION
localEM/NAMESPACE
localEM/R
localEM/R/excProbFun.R localEM/R/kentuckyData.R localEM/R/kernMatUtils.R localEM/R/lemEstFun.R localEM/R/lemXvEstUtils.R localEM/R/lemXvFun.R localEM/R/rasterPartFun.R localEM/R/smoothMatFun.R localEM/R/smoothMatUtils.R
localEM/build
localEM/build/vignette.rds
localEM/data
localEM/data/datalist
localEM/data/kMap.RData
localEM/data/kentuckyCounty.RData
localEM/data/kentuckyTract.RData
localEM/inst
localEM/inst/dataSource
localEM/inst/dataSource/usaPopulation.R
localEM/inst/doc
localEM/inst/doc/kentucky.Rmd
localEM/inst/doc/kentucky.html
localEM/localEM.Rproj
localEM/man
localEM/man/excProb.Rd localEM/man/kMap.Rd localEM/man/kentuckyCounty.Rd localEM/man/kentuckyTract.Rd localEM/man/lemXv.Rd localEM/man/rasterPartition.Rd localEM/man/riskEst.Rd localEM/man/smoothingMatrix.Rd
localEM/vignettes
localEM/vignettes/kentucky.Rmd
localEM/vignettes/toCleanMakefile

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