MFT.filterdata: MFT.filterdata
In MFT: The Multiple Filter Test for Change Point Detection

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/MFT.filterdata.R

Naive routine to remove trend from the data.

1	MFT.filterdata(x, filterwidth = NULL, filtersigma = NULL)

`x`	numeric vector, input sequence of random variables.
`filterwidth`	postive interger, < length(x)/2, number of data points left and right of the current value that are taken into account for Gaussian smoothing.
`filtersigma`	numeric, > 0, standard deviation of Gassian kernel.

invisible

`xfiltered`	filtered data (for filtering the first and last (filterwidth many) data points of the original series cannot be evaluated and are omited)
`xraw`	orignal data, but the first and last (filterwidth many) data point are omitted
`xtrend`	trend that is removed by filtering. That is xfiltered = xraw - xtrend
`x`	orignal data
`filterwidth`	number of data points left and right of the current value that are taken into account for Gaussian smoothing
`filtersigma`	standard deviation of the Gaussian kernel

Michael Messer, Stefan Albert, Solveig Plomer and Gaby Schneider

Michael Messer, Hendrik Backhaus, Albrecht Stroh and Gaby Schneider (2019+). Peak detection in times series

MFT.peaks, plot.MFT, summary.MFT, MFT.rate, MFT.variance, MFT.mean

set.seed(0)
# Normally distributed sequence with negative trend
x <- rnorm(1000,mean=seq(5,0,length.out=1000))
MFT.filterdata(x)
MFT.filterdata(x,filterwidth=200,filtersigma=200)