Median absolute deviation (MAD) outlier in Time Series
hampel(x, k, t0 = 3)
numeric vector representing a time series
threshold, default is 3 (Pearson's rule), see below.
The ‘median absolute deviation’ computation is done in the
vicinity of each point at least
k steps away from the end points of
At the lower and upper end the time series values are preserved.
A high threshold makes the filter more forgiving, a low one will declare
more points to be outliers.
t0<-3 (the default) corresponds to Ron
Pearson's 3 sigma edit rule,
t0<-0 to John Tukey's median filter.
Returning a list
L$y the corrected time series and
L$ind the indices of outliers in the ‘median absolut deviation’
Don't take the expression outlier too serious. It's just a hint to values in the time series that appear to be unusual in the vicinity of their neighbors under a normal distribution assumption.
Pearson, R. K. (1999). “Data cleaning for dynamic modeling and control”. European Control Conference, ETH Zurich, Switzerland.
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