Description Usage Arguments Value Author(s) References See Also Examples
Given the parameters of a multivariate normal distribution, aout.mvnorm
identifies α-outliers in a given data set.
1 | aout.mvnorm(data, param, alpha = 0.1, hide.outliers = FALSE)
|
data |
a data.frame or matrix. The data set to be examined. |
param |
a list. Contains the parameters of the normal distribution: the mean vector μ and the covariance matrix σ. |
alpha |
an atomic vector. Determines the maximum amount of probability mass the outlier region may contain. Defaults to 0.1. |
hide.outliers |
boolean. Returns the outlier-free data if set to |
Data frame of the input data and an index named is.outlier
that flags the outliers with TRUE
. If hide.outliers is set to TRUE
, a data frame of the outlier-free data.
A. Rehage
Kuhnt, S.; Rehage, A. (2013) The concept of α-outliers in structured data situations. In C. Becker, R. Fried, S. Kuhnt (Eds.): Robustness and Complex Data Structures. Festschrift in Honour of Ursula Gather. Berlin: Springer, 91-108.
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