Outlier Detection for Time Series Based on Distance and DF-RLS
Chen Qiana · Jisuanji gongcheng · 2012
In order to detect both Additive Outliers(AO) and Innovation Outliers(IO) in time series,this paper improves the linear prediction of time series,proposes a Distance Factor Recursive Least Square(DF-RLS) algorithm.It combines DF-RLS with distance-based outlier detection method,proposes a time series outlier detection method based on distance and DF-RLS,named DDR-OD.Experimental results show that the DDR-OD is an effective method for time series outlier detection.