findOutlyingPoints: Find outlying occurrence data

In cmerow/occOutliers: Identify Outlying Species Occurrence Records

Find outlying occurrence data

Description

Spatial or environmental outliers

Usage

findOutlyingPoints(
  pres,
  spOutliers = TRUE,
  envOutliers = TRUE,
  method = "grubbs",
  pval = 1e-05,
  checkPairs = TRUE,
  kRosner = 3,
  verbose = TRUE
)

Arguments

pres	a 'SpatialPoints' or 'SpatialPointsDataFrame' object describing the locations of species records. A 'SpatialPointsDataFrame' containing the values of environmental variables to be used must be supplied if 'envOutliers=TRUE'
spOutliers	logical; perform spatial outlier analysis
envOutliers	logical; perform environmental outlier analysis
method	character; options are 'iqr', 'grubbs', 'dixon', 'rosner'. Only a single value can be used; if mutliple tests are desired, call 'findOuliers' multiple times specifying different methods.
pval	user-specified p-value for assessing the significance of Grubbs test statistic.
checkPairs	logical; check for a single pair of outliers using the Grubbs test. This can only be performed for sample sizes <30. Only a single test is used because repeating it tends to throw out more points than seem reasonable, by eye. The value has no effect unless ‘method=’grubbs''.
kRosner	integer between 1 and 10. Determines the number of outliers suspected with a Rosner test. The value has no effect unless ‘method=’rosner''.
verbose	logical; print messages

Details

See Examples.

Value

Returns the SpatialPointsDataFrame provided with additional logical columns indicating spatial outliers (‘spOutliers') and environmental outliers (’'envOutliers').

Author(s)

Cory Merow <[e-mail]>

Examples

myPres=read.csv(system.file('extdata/SpeciesCSVs/Camissonia_tanacetifolia.csv',
                            package='occOutliers'))
myPres=myPres[complete.cases(myPres),]
sp::coordinates(myPres)=c(1,2)
myEnv=raster::stack(system.file('extdata/AllEnv.tif',package='occOutliers'))
names(myEnv)=read.table(system.file('extdata/layerNames.csv',package='occOutliers'))[,1]
myPresDF=sp::SpatialPointsDataFrame(myPres,data.frame(raster::extract(myEnv,myPres)))
presOut=findOutlyingPoints(pres=myPresDF,
                           spOutliers=TRUE,
                           envOutliers=TRUE,
                           pval=1e-5)
world.shp=readRDS(system.file('extdata/worldShpMollwide.rds',package='occOutliers'))
plotOutliers(presOut,shpToPlot = world.shp)

cmerow/occOutliers documentation built on July 8, 2023, 8:04 a.m.