zscore: Computes z-scores to flag environmental outliers.

In specleanr: Detecting Environmental Outliers in Data Analysis Pipelines

Computes z-scores to flag environmental outliers.

Description

Computes z-scores to flag environmental outliers.

Usage

zscore(
  data,
  var,
  output = "outlier",
  type = "mild",
  mode = "soft",
  pc = FALSE,
  pcvar = NULL,
  boot = FALSE
)

Arguments

data	Dataframe or vector to check for outliers.
var	Variable considered in flagging suspicious outliers.
output	Either clean: for data frame with no suspicious outliers or outlier: to return dataframe with only outliers.
type	Either mild if zscore cut off is 2.5 or extreme if zscore is >3.
mode	Either robust, if a robust mode is used which uses median instead of mean and median absolute deviation from median.
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

Details

The method uses mean as an estimator of location and standard deviation for scale (Rousseeuw & Hubert 2011), which both have zero breakdown point, and their influence function is unbounded (robustness of an estimator to outliers) (Seo 2006; Rousseeuw & Hubert 2011). Because both parameters are not robust to outliers, it leads to outlier masking and swamping (Rousseeuw & Hubert 2011). Records are flagged as outliers if their Z-score exceeds 2.5 (Rousseeuw & Hubert 2011).

Value

Data frame with or with no outliers.

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)

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

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