Time series outlier detection (a simple R function)

(By Andrea Venturini) Imagine you have a lot of time series – they may be short ones – related to a lot of different measures and very little time to find outliers. You need something not too sophisticated to solve quickly the mess. This is – very shortly speaking – the typical situation in which you can adopt washer.AV() function in R language. In this linked document (washer) you have the function and an example of actual application in R language:  a data.frame (dati) with temperature and rain (phen) measures (value) in 4 periods of time (time) and in 20 geographical zones (zone). (20*4*2=160  arbitrary observations). > dati           phen time zone value 1   Temperature    1  a01   2.0 2   Temperature    1  a02  20.0 … … 160        Rain    4  a20   8.5   The example of 20 meteorological stations measuring rainfall and temperature is useful to understand in which situation you can implement the washer() methodology. This methodology considers only 3 observations in a group of time series, for instance all 20 terns between time 2 and 4: if the their shape is similar between each other than no outlier will be detected, otherwise – as it happens to the orange time […]

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