detect_anoms_sd: Outlier detection

In JinmiaoChenLab/ClusterX: Fast clustering by automaticly search and find of density peaks

Description

Using generialized ESD to detect outliers, iterate and remove point with ares higher than lamda in a univariate data set assumed to come from a normally distributed population.

Usage

detect_anoms_sd(data, max_anoms = 0.1, alpha = 0.01, direction = "pos")

Arguments

data	A vectors of boservations.
max_anoms	Maximal percentile of anomalies.
alpha	The level of statistical significance with which to accept or reject anomalies.
direction	Directionality of the anomalies to be detected. Options are: 'pos' | 'neg' | 'both'.

Value

A vector containing indexes of the anomalies (outliers).

JinmiaoChenLab/ClusterX documentation built on May 7, 2019, 10:52 a.m.