adore.filter.madore.filter(Y, byrow=FALSE, min.width=10, max.width=200, test.sample.size=min.width/2, width.search="geometric", rtr.size=min.width, alpha=0.1, NA.sample.size=min.width, minNonNAs=min.width/2)madore.filter returns an object of class madore.filter. An object of class madore.filter is a list containing the following components:Y, and the settings used for the analysis are returned as the list members byrow, min.width, max.width, start.width, test.sample.size, width.search, rtr.size, extr.delay, NA.sample.size, and minNonNAs. Application of the function plot to an object of class madore.filter returns a plot showing the original multivariate time series with the filtered output.madore.filter is based on Repeated Median regression (Siegel, 1982) in moving time windows and serves for separating signals from noise and outliers in multivariate time series. At each time point $t$ the test procedure of the adaptive online Repeated Median filter (Schettlinger, Fried, Gather, 2008) is used to determine an appropriate window width $n(t)$ in [min.width, max.width]. Then the signal vector at time $t$ is estimated within the time window $(t-n(t)+1,\ldots,t)$ by a slight modification of the multivariate Trimmed Repeated Median-Least Squares regression (Lanius, Gather, 2004). A more detailed description of the madore.filter can be found in Borowski, Schettlinger, Gather (2009).robreg.filter, adore.filter.data(multi.ts)
extr <- madore.filter(multi.ts)
plot(extr)Run the code above in your browser using DataLab