Masking and Swamping effects in multivariate detection.

Masking: anomalies hide each other; Swamping: normal points look like anomalies[cite: 1].

Masking happens when multiple anomalies shift the mean/covariance. Swamping happens when anomalies increase the variance so much that normal points fall outside the limit[cite: 1].