Mixed Interquartile range and semiInterquartile range Walker et al., 2018

Mixed Interquartile range and semiInterquartile range Walker et al., 2018

Usage

mixediqr(data, var, output, x = 3, 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.
x: A constant for flagging outliers Walker et al., 2018).
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

Either clean our outliers

References

Walker ML, Dovoedo YH, Chakraborti S, Hilton CW. 2018. An Improved Boxplot for Univariate Data. American Statistician 72:348-353. American Statistical Association.

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)

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

# }