Add to ORKGLow-complexity robust modifications to the Tukey boxplot based on fast highly efficient robust estimates of scale are proposed. The performance of the Tukey boxplot and its modified robust versions is measured relative to identi- fication of outliers in Monte Carlo experiments at contaminated normal distri- butions. The obtained results show that the proposed methods outperform the conventional Tukey boxplot and the classical Grubbs test
We propose a procedure for computing a fast approximation to regression estimates based on the minim...
Whether an extreme observation is an outlier or not depends strongly on the corresponding tail behav...
It is evident from the comments by Bernoulli (1777) that the history of outliers is very old and tra...
Low-complexity robust modifications to the Tukey boxplot based on fast highly efficient robust esti...
Tukey’s boxplot is very popular tool for detection of outliers. It reveals the location, spread an...
Tukey’s boxplot is very popular tool for detection of outliers. It reveals the location, spread and ...
Tukey's traditional boxplot (Tukey, 1977) is a widely used Exploratory Data Analysis (EDA) tools oft...
A boxplot, also known as a box and whisker diagram, is a well-known graphing technique that displays...
In this paper we propose a method for correctly detecting outliers based on a new technique develope...
In this paper we suggest a simple way of constructing a bivariate boxplot based on convex hull peeli...
Standard statistical techniques such as least squares regression are very accurate if the underlying...
This paper concerns itself with the methods of identifying outliers in an otherwise normally distrib...
contaminated with outliers that should be eliminated before estimation of the reference interval. A ...
The classical estimators of multivariate location and scatter for the normal model are the sample m...
Efficient detection of outliers from massive data with a high outlier ratio is challenging but not e...
We propose a procedure for computing a fast approximation to regression estimates based on the minim...
Whether an extreme observation is an outlier or not depends strongly on the corresponding tail behav...
It is evident from the comments by Bernoulli (1777) that the history of outliers is very old and tra...
Low-complexity robust modifications to the Tukey boxplot based on fast highly efficient robust esti...
Tukey’s boxplot is very popular tool for detection of outliers. It reveals the location, spread an...
Tukey’s boxplot is very popular tool for detection of outliers. It reveals the location, spread and ...
Tukey's traditional boxplot (Tukey, 1977) is a widely used Exploratory Data Analysis (EDA) tools oft...
A boxplot, also known as a box and whisker diagram, is a well-known graphing technique that displays...
In this paper we propose a method for correctly detecting outliers based on a new technique develope...
In this paper we suggest a simple way of constructing a bivariate boxplot based on convex hull peeli...
Standard statistical techniques such as least squares regression are very accurate if the underlying...
This paper concerns itself with the methods of identifying outliers in an otherwise normally distrib...
contaminated with outliers that should be eliminated before estimation of the reference interval. A ...
The classical estimators of multivariate location and scatter for the normal model are the sample m...
Efficient detection of outliers from massive data with a high outlier ratio is challenging but not e...
We propose a procedure for computing a fast approximation to regression estimates based on the minim...
Whether an extreme observation is an outlier or not depends strongly on the corresponding tail behav...
It is evident from the comments by Bernoulli (1777) that the history of outliers is very old and tra...