Resistant outlier rules and the non-Gaussian case
Computational Statistics & Data Analysis
Statistical Models in S
Identifying outliers with sequential fences
Computational Statistics & Data Analysis
A robust estimator for the tail index of Pareto-type distributions
Computational Statistics & Data Analysis
Robust measures of tail weight
Computational Statistics & Data Analysis
Robust PCA for skewed data and its outlier map
Computational Statistics & Data Analysis
Malicious user detection in a cognitive radio cooperative sensing system
IEEE Transactions on Wireless Communications
Estimation of extreme percentiles in Birnbaum-Saunders distributions
Computational Statistics & Data Analysis
Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance
Applied Stochastic Models in Business and Industry
Generalized Birnbaum-Saunders kernel density estimators and an analysis of financial data
Computational Statistics & Data Analysis
Detecting influential data points for the Hill estimator in Pareto-type distributions
Computational Statistics & Data Analysis
On diagnostics in double generalized linear models
Computational Statistics & Data Analysis
Multivariate measurement error models using finite mixtures of skew-Student t distributions
Journal of Multivariate Analysis
| Hi-index | 0.04 |
The boxplot is a very popular graphical tool for visualizing the distribution of continuous unimodal data. It shows information about the location, spread, skewness as well as the tails of the data. However, when the data are skewed, usually many points exceed the whiskers and are often erroneously declared as outliers. An adjustment of the boxplot is presented that includes a robust measure of skewness in the determination of the whiskers. This results in a more accurate representation of the data and of possible outliers. Consequently, this adjusted boxplot can also be used as a fast and automatic outlier detection tool without making any parametric assumption about the distribution of the bulk of the data. Several examples and simulation results show the advantages of this new procedure.