purge: Remove outliers

In rushkin/outlieR: Outlier detection in multidimensional data

Description

Remove detected outliers in a multidimensional data set

Usage

purge(x, flag = NULL, level = 0.1, nmax = NULL, side = NULL,
  crit = "lof", k = 5, metric = "euclidean", q = 3)

Arguments

x	a matrix, data frame or vector of data points (a vector will be understood as 1D data, equivalent to a 1-column matrix). Each row is a data point and each column is a dimension. NA values are allowed and will produce NAs in the output.
flag	a boolean or integer (0-or-1) vector flagging outliers, such as produced by the function flag. If NULL, further arguments will be used to compute it here by calling flag.
level	passed to the function flag if the argument 'flag' is NULL or missing
nmax	passed to the function flag if the argument 'flag' is NULL or missing
side	passed to the function flag if the argument 'flag' is NULL or missing
crit	passed to the function flag if the argument 'flag' is NULL or missing
k	passed to the function flag if the argument 'flag' is NULL or missing
metric	distance metric to be used in LOF (if flag is not provided). A choice of 'euclidean','maximum','manhattan','canberra','minkowski', or 'binary'. Any unambiguous substring can be given, case insensitive.
q	power in Minkowski metric, used if fill='median' and metric='minkowski'

Details

The output object will be a vector, a matrix or a data-frame, depending on what x was. Row names, column names or (if x was a named vector) names will be kept.

Value

object like x but with outliers removed.

rushkin/outlieR documentation built on Dec. 20, 2020, 6:11 a.m.