| mergeBugsData {diseasemapping} | R Documentation |
merge the result from bugs function
mergeBugsData(x, bugsSummary, by.x = NULL, newcol = "mean", ...) ## S3 method for class 'SpatialPolygonsDataFrame': mergeBugsData(x, bugsSummary, by.x=NULL, newcol="mean", ...) ## S3 method for class 'data.frame': mergeBugsData(x, bugsSummary, by.x=NULL, newcol="mean", ...)
x |
spatial polygon object i.e population data set (popdata) |
bugsSummary |
posterior distribution result from summaryChain function |
by.x |
the common term from the spatial polygon object and the bugs function result |
newcol |
the summary statistic that to be merged back to the data frame |
... |
additional arguments |
Patrick Brown
#data(popdata)
#newdata = c("3560102"=2, "3560104"=3)
#popdatatry = mergeBugsData(popdata, newdata, by.x="CSDUID")
# if the data set is a spatial polygons data frame:
#popdatatry = mergeBugsData.SpatialPolygonsDataFrame(popdata, newdata, by.x="CSDUID")
# if the data set is a data frame
#popdatatry = mergeBugsData.data.frame(popdata, newdata, by.x="CSDUID")
## Not run:
library(glmmBUGS)
data(popdata)
data(casedata)
therates = getRates(casedata, popdata, ~age*sex)
ontario = getSMR(popdata, therates, casedata)
ontario@data = ontario@data[,c("CSDUID","observed","logExpected")]
library(spdep)
popDataAdjMat = poly2nb(ontario, ontario[["CDSUID"]])
library(glmmBUGS)
forBugs = glmmBUGS(formula=observed + logExpected ~ 1,
effects="CSDUID", family="poisson", spatial=popDataAdjMat,
data=ontario@data)
startingValues = forBugs$startingValues
source("getInits.R")
library(R2WinBUGS)
ontarioResult = bugs(forBugs$ragged, getInits, parameters.to.save = names(getInits()),
model.file="model.bug", n.chain=3, n.iter=100, n.burnin=10, n.thin=2,
program="winbugs", debug=TRUE)
data(ontarioResult)
ontarioParams = restoreParams(ontarioResult, forBugs$ragged)
ontarioSummary = summaryChain(ontarioParams)
ontario = mergeBugsData(ontario, ontarioSummary)
## End(Not run)