knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-" )
The sparr
package for R provides functions to estimate fixed and adaptive kernel-smoothed
spatial relative risk surfaces via the density-ratio method and perform subsequent inference.
Fixed-bandwidth spatiotemporal density and relative risk estimation is also supported.
This package is available on CRAN, and we recommend installing it from there using the standard
install.packages('sparr')
If you wish to live on the bleeding edge, you may install from github using devtools
:
# install.packages("devtools") devtools::install_github('tilmandavies/sparr')
This is a basic example of relative risk estimation for primary biliary cirrhosis cases from north east England.
# Load library library(sparr) # Load data on cases of primary biliary cirrhosis from north east England data(pbc) # Split into cases and controls pbc_case <- split(pbc)$case pbc_cont <- split(pbc)$control # Estimate global bandwidth for smoothing h0 <- OS(pbc, nstar="geometric") # Compute a symmetric (pooled) adaptive relative risk estimate # with tolerance contours pbc_rr <- risk(pbc_case, pbc_cont, h0=h0, adapt=TRUE, tolerate=TRUE, hp=OS(pbc)/2, pilot.symmetry="pooled", davies.baddeley=0.05) # And produce a plot plot(pbc_rr)
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