adjustboxplots: Adjust the boxplots bounding fences using medcouple to flag...

In specleanr: Detecting Environmental Outliers in Data Analysis Pipelines

Adjust the boxplots bounding fences using medcouple to flag suspicious outliers.

Description

Adjust the boxplots bounding fences using medcouple to flag suspicious outliers.

Usage

adjustboxplots(
  data,
  var,
  output = "outlier",
  a = -4,
  b = 3,
  coef = 1.5,
  pc = FALSE,
  pcvar = NULL,
  boot = FALSE
)

Arguments

data	dataframe. Dataframe to check for outliers.
var	string. Environmental predictor considered in flagging suspicious outliers.
output	string Either clean: for dataframe with no suspicious outliers or outlier: to return dataframe with only outliers.
a	numeric. Constant for adjusted boxplots.
b	numeric. Constant for adjusted boxplots.
coef	numeric. Constant for adjusted boxplots.
pc	Whether principal component analysis will be computed. Default FALSE
pcvar	Principal component analysis to e used for outlier detection after PCA. Default PC1
boot	Whether bootstrapping will be computed. Default FALSE

Value

dataframe. Dataframe with or with no outliers.

References

Hubert M, Vandervieren E. 2008. An adjusted boxplot for skewed distributions. Computational Statistics and Data Analysis 52:5186-5201.

Examples

data("efidata")

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 = efidata, raster= wcd ,
                      lat = 'decimalLatitude', lon= 'decimalLongitude',
                       colsp = "scientificName",
                       bbox = db,
                       minpts = 10)

adout <- adjustboxplots(data = refdata[["Thymallus thymallus"]], var = 'bio6', output='outlier')

specleanr documentation built on Nov. 26, 2025, 1:07 a.m.