z_score_method: z_score_method

In OutliersLearn: Educational Outlier Package with Common Outlier Detection Algorithms

z_score_method

Description

This function implements the outlier detection algorithm using standard deviation and mean

Usage

z_score_method(data, d, tutorialMode)

Arguments

data	Input Data that will be processed with or without the tutorial mode activated
d	Degree of outlier or distance at which an event is considered an outlier
tutorialMode	if TRUE the tutorial mode is activated (the algorithm will include an explanation detailing the theory behind the outlier detection algorithm and a step by step explanation of how is the data processed to obtain the outliers following the theory mentioned earlier)

Value

None, does not return any value

Author(s)

Andres Missiego Manjon

Examples

inputData = t(matrix(c(3,2,3.5,12,4.7,4.1,5.2,
4.9,7.1,6.1,6.2,5.2,14,5.3),2,7,dimnames=list(c("r","d"))))
inputData = data.frame(inputData)
z_score_method(inputData,2,FALSE) #Can be changed to TRUE

OutliersLearn documentation built on June 22, 2024, 10:23 a.m.