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

Value

Dataframe or vector with or without outliers

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 ()

References

Schwertman NC, de Silva R. 2007. Identifying outliers with sequential fences. Computational Statistics and Data Analysis 51:3800-3810.
Schwertman NC, Owens MA, Adnan R. 2004. A simple more general boxplot method for identifying outliers. Computational Statistics and Data Analysis 47:165-174.
Dastjerdy B, Saeidi A, Heidarzadeh S. 2023. Review of Applicable Outlier Detection Methods to Treat Geomechanical Data. Geotechnics 3:375-396. MDPI AG.

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)

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