do_outl_degree: Degree of outlierness

In adamethods: Archetypoid Algorithms and Anomaly Detection

Description

Classification of outliers according to their degree of outlierness. They are classified using the tolerance proportion. For instance, outliers from a 95

Usage

do_outl_degree(vect_tol = c(0.95, 0.9, 0.85), resid_vect, alpha = 0.05, 
               outl_degree = c("outl_strong", "outl_semi_strong", "outl_moderate"))

Arguments

vect_tol	Vector the tolerance values. Default c(0.95, 0.9, 0.85).
resid_vect	Vector of n residuals, where n was the number of rows of the data matrix.
alpha	Significance level. Default 0.05.
outl_degree	Type of outlier to identify the degree of outlierness. Default c("outl_strong", "outl_semi_strong", "outl_moderate").

Value

List with the type outliers.

Author(s)

Guillermo Vinue

See Also

outl_toler

Examples

do_outl_degree(0.95, 1:100, 0.05, "outl_strong")
                                                     

adamethods documentation built on Aug. 4, 2020, 5:08 p.m.