runFieldModelUtazi: Run a Model and Estimate Underlying Field From Point and...

In nmmarquez/PointPolygon: Evaluate Point and Polygon Data Simulatneously

Description

Run a model and estimate underlying latent and probability field from point and polygon data using INLA and Utazi method.

Usage

runFieldModelUtazi(field, pointDF = NULL, polyDF = NULL, moption = 0,
  verbose = FALSE, symbolic = TRUE, control = list(eval.max = 10000,
  iter.max = 10000), rWidth = NULL, aggData = TRUE, shape3 = NULL)

Arguments

field	field object which simulated underlying data
pointDF	data simulated from samplePoints
polyDF	data simulated from samplePolygns
moption	int, intger indicating how polygon data should be estimated 0 approach.
verbose	logical, print model fitting information
symbolic	logical, use metas reordering in model fitting
control	list, control list passed to nlminb
rWidth	int, only used in moption 2 to build besag prior
aggData	bool, whether to aggregate data as passed in
shape3	the shape to build the adjaceny matrix with

Value

List of fitted model objects.

Examples

## Not run: 
unitSim <- simField(
N = 500, rangeE = .7,
offset = c(0.1, 0.2), 
max.edge = c(0.1,0.2),
beta0 = -2,
betaList = list(
    list(type="random", value=2),
    list(type="spatial", value=-.5),
    list(type="cluster", value=-2)
))

polyDF <- samplePolygons(unitSim, round(1200*100/9), rWidth=3)

runFieldModelUtazi(unitSim, polyDF=polyDF, moption=2, rWidth=3)


## End(Not run)

nmmarquez/PointPolygon documentation built on Dec. 10, 2020, 1:15 a.m.