ggoutlieraccum: 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"
)

Value

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

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.