ggoutlieraccum: Identify if enough methods are selected for the outlier...

In specleanr: Detecting Environmental Outliers in Data Analysis Pipelines

Identify if enough methods are selected for the outlier detection.

Description

Identify if enough methods are selected for the outlier detection.

Usage

ggoutlieraccum(
  x,
  boots = 5,
  select = NULL,
  ncol = 3,
  linecolor = "blue",
  seed = 1134,
  sci = FALSE,
  xlab = "Number of methods",
  ylab = "Number of outliers",
  scales = "free"
)

Arguments

x	datacleaner. The output from the outlier detection in multidetect function.
boots	interger. The number of bootstraps to sample the outliers obtained during outlier detection process. Start from a lower number such as 10 and increase serially to get a smoother curve. High bootstrap may lead to crashing the Generalized Additive Model used to fit the bootstraps and cumulative number of outliers.
select	vector. If more than 10 groups are considered, then the at least should be seclected to hvae meaningful visualization.
ncol	integer. Number of columns if the groups are greater 4, to allow effective vizualisation.
linecolor	string A parameter to indicate the color of the lines. The default is 'purple'.
seed	integer To fix the random sampling during bootstrapping.
sci	logical. If sci is TRUE, then the species names will be italised otherwise normal names will displayed. Default FALSE
xlab, ylab	string. inherited from ggplot2 to changes x and y axis texts.
scales	string Define if the x oy y axis will be shared or free. check ggplot2 for details.

Value

ggplot2 output with cumulative number of outliers and number of methods used.

specleanr documentation built on Nov. 26, 2025, 1:07 a.m.