prepareInput {GeoAdjust}

Prepares input data list for the model estimation with estimateModel() function.

Description

Prepares input data list for the model estimation with estimateModel() function.

Usage

prepareInput(
  response = NULL,
  locObs = NULL,
  likelihood,
  jScale = 1,
  urban = NULL,
  mesh.s = NULL,
  adminMap = NULL,
  covariateData = NULL,
  target_crs
)

Arguments

response

A list containing the number of trials (ns) and number of successes (ys) for the binomial model, response values (ys) for the Gaussian model or the Poisson counts for the Poisson model.

locObs

An sf class multipoint object containing the coordinates of DHS survey cluster centers. (It should contain the crs information.)

likelihood

A value indicating which likelihood model should be used (0, 1 or 2 for Gaussian, binomial or Poisson, respectively).

jScale

Jittering scale, where 1 represents the default DHS jittering scheme. It allows experimenting with larger jittering scales. Otherwise should remain as 1.

urban

A vector containing the urbanization classification of the administrative area that each cluster center is initially located within (U for urban and R for rural).

mesh.s

A triangulation mesh. It should be constructed in the target_crs.

adminMap

An sf class multipolygon object. It contains the borders of the administrative area level that was respected while the cluster centers were initially being jittered (can be obtained from https://gadm.org). It should contain crs information.

covariateData

A list containing the covariates as SpatRaster objects. Each SpatRaster should contain the crs information.

target_crs

A projection string representing the desired coordinate reference system according to which, the integration rings and integration points will be located. The measurement unit of the target_crs should be in kilometers.

Value

A list containing the data input for estimateModel() function.

Examples

path1 <- system.file("extdata", "geoData.rda", package = "GeoAdjust")
path2 <- system.file("extdata", "exampleMesh.rda", package = "GeoAdjust")
load(path1)
load(path2)
crs_KM = "+units=km +proj=utm +zone=37 +ellps=clrk80 +towgs84=-160,-6,-302,0,0,0,0 +no_defs"
crs_Degrees = "+proj=longlat +datum=WGS84"
locObs = data.frame(long = surveyData$long, lat = surveyData$lat)
locObs = sf::st_as_sf(locObs, coords=c("long","lat"), crs = crs_Degrees)
inputData <- prepareInput(response = list(ys = surveyData$ys, ns = surveyData$ns),
locObs = locObs, likelihood = 1, jScale = 1,
urban = surveyData$urbanRural, mesh.s = exampleMesh, adminMap = adm1,
covariateData = NULL, target_crs = crs_KM)