Analytics for the Internet of Things (IoT)

Anomaly detection using R

Anomaly detection is a way to use historical data to identify unusual observations without requiring a labeled training set. Modern anomaly detection methods take into account long-term trends and cyclical variation in the data while determining which observations to flag as anomalies.

Twitter has recently released an advanced open source anomaly detection package for R called AnomalyDetection. It is geared toward detecting anomalies in single value high frequency (less than a day) time series data; however, it is possible to set an option to handle datasets longer than a month. It can also be used on a vector of non-time series data.

It is good at handling the effects of trends and seasonality - although seasonality, ...