Often the geographic coordinates of occurrence records are subject to uncertainty. One approach ot accounting for that uncertainty in an SDM analysis is to run several analyses, each time sampling a different location from a probability distribution over the likely "true" coordinates. JitterOccurrence
generates one such sample, under an assumption that the distribution is an isotropic Gaussian with standard deviation sd
JitterOccurrence(.data, sd = 0)
.data
is a list of a data frame and a raster object returned from occurrence modules and covariate modules respectively. .data
is passed automatically in workflow from the occurrence and covariate modules to the process module(s) and should not be passed by the user.Currently only a single standard deviation is provided for all occurrence records. Future iterations of this module will enable more control over the uncertainty distributions
presence-only, presence/absence, presence/background, abundance, proportion
0.1
2016-06-16
Other process: AddRandomUniformPredictors
,
BackgroundAndCrossvalid
,
Background
, Bootstrap
,
Clean
, Crossvalidate
,
MESSMask
, NoProcess
,
OneHundredBackground
,
OneThousandBackground
,
PartitionDisc
,
StandardiseCov
,
TargetGroupBackground
,
Transform
, addInteraction