dshape3dProp {Kernelheaping}

3d Kernel density estimation for data classified in polygons or shapes

Description

3d Kernel density estimation for data classified in polygons or shapes

Usage

dshape3dProp(
  data,
  burnin = 2,
  samples = 5,
  shapefile,
  gridsize = 200,
  boundary = FALSE,
  deleteShapes = NULL,
  fastWeights = TRUE,
  numChains = 1,
  numThreads = 1
)

Arguments

data

data.frame with 5 columns: x-coordinate, y-coordinate (i.e. center of polygon) and number of observations in area for partial population and number of observations for complete observations and third variable (numeric).

burnin

burn-in sample size

samples

sampling iteration size

shapefile

shapefile with number of polygons equal to nrow(data) / length(unique(data[,5]))

gridsize

number of evaluation grid points

boundary

boundary corrected kernel density estimate?

deleteShapes

shapefile containing areas without observations

fastWeights

if TRUE weigths for boundary estimation are only computed for first 10 percent of samples to speed up computation

numChains

number of chains of SEM algorithm

numThreads

number of threads to be used (only applicable if more than one chains)