## ----include=FALSE------------------------------------------------------------ Sys.setenv(LANG = "en") ## ----------------------------------------------------------------------------- library(prevR, quietly = TRUE) col <- c( id = "cluster", x = "x", y = "y", n = "n", pos = "pos", c.type = "residence", wn = "weighted.n", wpos = "weighted.pos" ) dhs <- as.prevR(fdhs.clusters, col, fdhs.boundary) str(dhs) print(dhs) ## ---- eval = FALSE------------------------------------------------------------ # imported_data <- import.dhs("data.sav", "gps.dbf") ## ---- fig.width=6, fig.height=6----------------------------------------------- plot(dhs, main = "Clusters position") plot(dhs, type = "c.type", main = "Clusters by residence") plot(dhs, type = "count", main = "Observations by cluster") plot(dhs, type = "flower", main = "Positive cases by cluster") ## ---- fig.width=6, fig.height=6----------------------------------------------- plot(dhs, axes = TRUE) dhs <- changeproj( dhs, "+proj=utm +zone=30 +ellps=WGS84 +datum=WGS84 +units=m +no_defs" ) print(dhs) plot(dhs, axes = TRUE) ## ---- include=FALSE----------------------------------------------------------- qa <- quick.prevR( fdhs, return.results = TRUE, return.plot = TRUE, plot.results = FALSE, progression = FALSE ) ## ---- eval=FALSE-------------------------------------------------------------- # quick.prevR(fdhs) ## ---- echo=FALSE, fig.width=6, fig.height=6----------------------------------- qa$plot ## ---- fig.width=8, fig.height=4----------------------------------------------- res <- quick.prevR( fdhs, N = c(100, 200, 300), return.results = TRUE, return.plot = TRUE, plot.results = FALSE, progression = FALSE, nb.cells = 50 ) res$plot ## ---- fig.width=6, fig.height=6----------------------------------------------- # Calculating rings of the same number of observations for different values of N dhs <- rings(fdhs, N = c(100, 200, 300, 400, 500), progression = FALSE) print(dhs) summary(dhs) # Prevalence surface for N=300 prev.N300 <- kde(dhs, N = 300, nb.cells = 200, progression = FALSE) plot( prev.N300["k.wprev.N300.RInf"], pal = prevR.colors.red, lty = 0, main = "Regional trends of prevalence (N=300)" ) # with ggplot2 library(ggplot2) ggplot(prev.N300) + aes(fill = k.wprev.N300.RInf) + geom_sf(colour = "transparent") + scale_fill_gradientn(colours = prevR.colors.red()) + labs(fill = "Prevalence (%)") + theme_prevR_light() # Surface of rings' radius radius.N300 <- krige("r.radius", dhs, N = 300, nb.cells = 200) plot( radius.N300, pal = prevR.colors.blue, lty = 0, main = "Radius of circle (N=300)" )