xyToRaster: Crate Shape object for a parameter estimated in a LopodModel

In bayesLopod: Bayesian Inference of Landscape Occupancy from Presence-Only Data

Description

Crate Shape object for a parameter estimated in a LopodModel

Usage

xyToRaster(xyRecords, xySamplingEffort, nrows = 50, extentExpansion = 0.1,
  extent = NULL, basemap = getData("worldclim", var = "alt", res = 10))

Arguments

xyRecords	Object of class SpatialPoints or SpatialPointsDataFrame with the locality-records of the species.
xySamplingEffort	Object of class SpatialPoints or SpatialPointsDataFrame with the coordinates of all sampling events (including those in which the species was found).
nrows	Number of rows that the final Raster will have. It will be use to determine its resolution.
extentExpansion	Factor by which the final extent should be expended. If 0 and extent is NULL, the final extent will be determined by the most extreme locality records. If extent is given, extentExpansion will be ignored.
extent	Object of class Extent delimiting the region to be included in the final raster
basemap	Object of class Raster in which cell with NA values will not be included. If NULL, all cells in the raster will be included.

Value

A Stack object with two layers: one for the number of records per cell ("samplingEffort"), and another one with the number of sampling events ("spDetections").

Examples

data("simSpRecords", package = "bayesLopod")
data("simSpSamplingEffort", package = "bayesLopod")
simSpRasters = xyToRaster(xyRecords = simSpRecords,xySamplingEffort = simSpSamplingEffort,
basemap = NULL, nrows = 50, extentExpansion = 0)

bayesLopod documentation built on Jan. 4, 2018, 5:08 p.m.