inst/doc/intro_prevR.R

In prevR: Estimating Regional Trends of a Prevalence from a DHS and Similar Surveys

## ----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)"
)