Probabilistic Anomaly Detection in Time Series Data

Implement a sophisticated JavaScript library for detecting statistical anomalies in time-series data streams, using advanced statistical techniques like Gaussian Mixture Models and Z-score normalization. The solution should support configurable sensitivity levels, handle multi-dimensional time series, and provide real-time streaming anomaly detection with low computational overhead. Include visualization components for rendering detected anomalies and supporting interpretability.