alphaOutlier (version 1.2.0)

aout.norm: Find $\alpha$-outliers in normal data

Description

Given the parameters of a normal distribution, aout.norm identifies $\alpha$-outliers in a given data set.

Usage

aout.norm(data, param = c(0, 1), alpha = 0.1, hide.outliers = FALSE)

Arguments

data

a vector. The data set to be examined.

param

a vector. Contains the parameters of the normal distribution: $\mu, \sigma$.

alpha

an atomic vector. Determines the maximum amount of probability mass the outlier region may contain. Defaults to 0.1.

hide.outliers

boolean. Returns the outlier-free data if set to TRUE. Defaults to FALSE.

Value

is.outlier that flags the outliers with TRUE. If hide.outliers is set to TRUE, a simple vector of the outlier-free data.

References

Gather, U.; Kuhnt, S.; Pawlitschko, J. (2003) Concepts of outlyingness for various data structures. In J. C. Misra (Ed.): Industrial Mathematics and Statistics. New Delhi: Narosa Publishing House, 545-585.

See Also

dnorm

Examples

# implosion breakdown point:
aout.norm(data = iris.setosa, param = c(median(iris.setosa), mad(iris.setosa)), 
          alpha = 0.01) 
# better:
aout.norm(data = iris.setosa, param = c(median(iris.setosa), sd(iris.setosa)), 
          alpha = 0.01)