sptotal (version 1.0.1)

geostatSim: Simulate geostatistical data on set of given locations

Description

Spatially correlated data are simulated assuming a multivariate normal random error vector. For simplicity, only "Exponential" and "Spherical" simulation options are given here.

Usage

geostatSim(
  loc.data,
  xcol = "x",
  ycol = "y",
  parsil = 1,
  range = 1,
  nugget = 0,
  minorp = 1,
  rotate = 90,
  extrap = NULL,
  CorModel = "Exponential"
)

Value

data.frame of three columns, the original location data appended with a 3rd column of simulated geostatistical data

Arguments

loc.data

data.frame with x- and y-coordinates of locations for simulated data

xcol

name of the column in loc.data with x-coordinates, default is "x"

ycol

name of the column loc.data with y-coordinates, default is "y"

parsil

partial sill of autocorrelation model, default = 1

range

range of autocorrelation model, default = 1

nugget

range of autocorrelation model, default = 0

minorp

proportion of range in x direction to that of y direction for unrotated anisotropic model, default = 1

rotate

rotation of anisotropic axes, default = 90

extrap

extra covariance parameter

CorModel

autocorrelation model, default = "Exponential". Other possibilities are "Spherical".

Author

Jay Ver Hoef

Examples

locations <- expand.grid(1:10, 1:10)
geostatSim(locations, xcol = "Var1", ycol = "Var2",
parsil = 4, range = 20, nugget = 1, CorModel = "Exponential")