sd_outliers: [!] Outlier detection based on standard deviations (sd)

In GegznaV/spHelper: Extension of Package `hyperSpec` and Various Convenience Functions

[!] Outlier detection based on standard deviations (sd)

Description

Detect elements in each column that are outside mean +/- n standard deviations and rows that contain at least one such element.

Usage

sd_outliers(x, n = 2)

outside_mean_pm_Nsd(x, n = 2)

Arguments

x	Matrix-like data or hyperSpec object.
n	A number of standard deviations.

Value

A list with these elements

• matrix - a logical matrix, with TRUE for elements which are outside column mean +/- n standard deiations;

• rows - a logical vector that indicate rows that have at least one such element.

Author(s)

Vilmantas Gegzna

See Also

mean_Nsd

Other spHelper utilities: IQR_outliers(), expr2text(), mad_outliers(), rmExpr(), subt(), unGroup(), uncall()

Other spHelper functions for spectroscopy and hyperSpec: IQR_outliers(), binning(), file, gapDer(), hy2mat(), hyAdd_Label_wl(), hyAdd_Labels_PAP_PD_2014(), hyAdd_Labels_TD2009(), hyAdd(), hyDrop_NA(), hyGet_palette(), hyRm_palette(), mad_outliers(), mean_Nsd(), median_Nmad(), plot_hyPalette(), prepare_PAP_RK_2014__MATLAB_failui(), read.OOIBase32(), read.OceanView.header(), read.OceanView(), read.sp.csv2(), read3csv2hy(), replace_spc(), spStat(), sp_class_perform()

Other outlier detection functions in spHelper: IQR_outliers(), mad_outliers()

GegznaV/spHelper documentation built on April 16, 2023, 1:42 p.m.