Distribution boxplot

Usage

distboxplot(
  data,
  var,
  output,
  p1 = 0.025,
  p2 = 0.975,
  boot = FALSE,
  pc = FALSE,
  pcvar = NULL
)

Arguments

data: Dataframe or vector where to check outliers.
var: Variable to be used for outlier detection if data is not a vector file.
output: Either clean: for clean data output without outliers; outliers: for outlier data frame or vectors.
p1, p2: Different pvalues for outlier detection Schwertman et al. 2004).
boot: Whether bootstrapping will be computed. Default FALSE
pc: Whether principal component analysis will be computed. Default FALSE
pcvar: Principal component analysis to e used for outlier detection after PCA. Default PC1

Value

Either clean or outliers.

Examples


if (FALSE) { # \dontrun{

data("efidata")

gbd <- check_names(data = efidata, colsp='scientificName', pct=90, merge=TRUE)

danube <- system.file('extdata/danube.shp.zip', package='specleanr')

db <- sf::st_read(danube, quiet=TRUE)

wcd <- terra::rast(system.file('extdata/worldclim.tiff', package='specleanr'))

refdata <- pred_extract(data = gbd, raster= wcd , lat = 'decimalLatitude', lon= 'decimalLongitude',
                          colsp = 'speciescheck',
                          bbox = db,
                          minpts = 10)

 bxout <- distboxplot(data = refdata[['Salmo trutta']], var = 'bio6', output='outlier')
} # }