Multivariate Outlier Detection Methods // Provides methods for detecting multivariate outliers in numeric datasets. The package implements classical Mahalanobis distance, robust Minimum Covariance Determinant (MCD), and Principal Component Analysis (PCA)-based approaches for outlier detection. The methodology is informed by Aggarwal (2017) doi:10.1007/978-3-319-47578-3 and Grentzelos, Caroni and Barranco-Chamorro (2020) doi:10.1002/cmm4.1129. Visualization functions are included to aid interpretation of detected outliers. Mahalanobis distance calculations are accelerated using 'C++' through 'Rcpp'.