This R package focuses on tools for detecting anomaly on a time series, using Bayesian contextual anomaly detection.

It has three main goals:

• Detect anomaly on time series

• Indentify the most important features needed for data analysis

• Provide automatic analysis that makes them easy to use from R

• .data: data table to be used

• .scope: training period, testing period, and KPI names

• .setting: algorithm setting

• .plans: combination of .scope and .setting

• .prior: prior values for model and formula tables for i.v. and d.v.

• .result

• Report for each analysis e.g.) check_model