Outlier detection class for multiple methods

Slots

result: List of data sets with outliers detected.
mode: Either ´TRUE´ for multiple species and FALSE for one species.
varused: The variable used for outlier detection, useful for univariate outlier detection methods.
out: Either outliers or clean dataset outputted.
methodsused: The methods used in outlier detection.
dfname: the dataframe name to aid tracking it during clean data extraction.
excluded: whether some columns were excluded during outlier detection. useful for multivariate methods where coordinates are removed from the data.
pc: parameters for principal component analysis.
bootstrap: parameters for bootstrapping for small data sets.
nboots: the number of bootstraps during bootstrapping.
pcvariable: variable to be considered during PCA.
pcretained: the number data columns retained. the default is 3.
maxrecords: the maximum number of records used for bootstrapping.