geozoning (version 1.0.0)

randKmap: randKmap: Generate data for zoning or prepare real data

Description

randKmap: Generate data for zoning or prepare real data

Usage

randKmap(DataObj, seed = NULL, nPoints = 450, nPointsK = 2000,
  nSimuCond = 0, typeMod = "Exp", Vpsill = 5, Vrange = 0.2, Vmean = 8,
  Vnugget = 0.2, boundary = list(x = c(0, 0, 1, 1, 0), y = c(0, 1, 1, 0,
  0)), manualBoundary = FALSE, krig = 2, disp = 0, FULL = FALSE)

Arguments

DataObj

=NULL: simulated data with seed or = a data frame with real data

seed

numeric, seed used to randomly generate data points

nPoints

numeric, number of raw data points, default 450

nPointsK

numeric, number of kriged data points, default 2000

nSimuCond

number of conditional simulations, reserved for future implementation.

typeMod

type of variogram model (see vgm) "Gau", "Sph", "Exp"

Vpsill

numeric, default 5

Vrange

numeric, default 0.2

Vmean

numeric, default 8

Vnugget

numeric, default 0

boundary

list contains x and y

manualBoundary

logical, default FALSE

krig

numeric

disp

numeric

FULL

logical, if TRUE the returned list is complete

Value

a list

rawData

simulated or real raw data within the boundary

step

grid step

krigData

kriged data as a SpatialPointsDataFrame

krigGrid

kriged data in form of a grid-useful for image plots.

krigN

list of neighbours of each kriged data point

krigSurfVoronoi

list of areas of Voronoi polygons in the tesselation of kriged data

modelGen

random fields model

VGMmodel

vgm model

boundary

(x,y) list of boundary points

ratio

ratio used to normalize x data

Details

Generates a map structure from simulated data or real data. Kriged data are normalized so that x-coordinates are between 0 and 1. y-coordinates are normalized with the same ratio used for x-coordinates. Kriging is either done with inverse distance interpolation, or with a variogram model. It creates a structure that contains the data and parameters necessary to perform a zoning. The structure is identical wether the data are simulated or not.

Examples

# NOT RUN {
map = randKmap(NULL,nPointsK=200,Vmean=15,krig=2)
mean(map$krigGrid) # mean of generated kriged data
plotMap(map)
# }