seqfences: Sequential fences method

In specleanr: Detecting Environmental Outliers in Data Analysis Pipelines

Sequential fences method

Description

Sequential fences method

Usage

seqfences(
  data,
  var,
  output,
  gamma = 0.95,
  mode = "eo",
  pc = FALSE,
  pcvar = NULL,
  boot = FALSE
)

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.
gamma	numeric. the p-values used to classify a record as an outlier. The lower the p-value, the extremeness is the outlier Schwertman & de Silva 2007.
mode	string. Indicates the extremeness of the outlier.
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

Sequential fences is a modification of the TUKEY boxplot, where the data is divided into groups each with its own fences Schwertman & de Silva 2007. The groups can range from 1, which flags mild outliers to 6 for extreme outliers ()

Value

Dataframe or vector with or without outliers

References

1. Schwertman NC, de Silva R. 2007. Identifying outliers with sequential fences. Computational Statistics and Data Analysis 51:3800-3810.

2. Schwertman NC, Owens MA, Adnan R. 2004. A simple more general boxplot method for identifying outliers. Computational Statistics and Data Analysis 47:165-174.

3. Dastjerdy B, Saeidi A, Heidarzadeh S. 2023. Review of Applicable Outlier Detection Methods to Treat Geomechanical Data. Geotechnics 3:375-396. MDPI AG.

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)

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

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