Detecting outliers for multivariate data is difficult and does not work by visual inspection.
Mahalanobis distance (MD) has been a classical method to detect outliers in multivariate …

In multivariate data, outliers are difficult to detect especially when the dimension of the data
increase. Mahalanobis distance (MD) has been one of the classical methods to detect …

Mahalanobis distance (MD) is a classical method to detect outliers for multivariate data.
However, classical mean and covariance matrix in MD suffered from masking and swamping …

Data in practice are often of high dimension and multivariate in nature. Detection of outliers
has been one of the problems in multivariate analysis. Detecting outliers in multivariate data …

In practice, multivariate data frequently include outliers. Since outliers can cause incorrect
conclusions, a robust estimator must be used to analyze the data as the robust estimator is …