specleanr (version 1.0.0)

adjustboxplots: 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
)

Value

dataframe. Dataframe with or with no outliers.

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

References

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

Examples

# \donttest{
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')

# }