MFT.filterdata {MFT} | R Documentation |
MFT.filterdata
Description
Naive routine to remove trend from the data.
Usage
MFT.filterdata(x, filterwidth = NULL, filtersigma = NULL)
Arguments
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. |
Value
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 |
Author(s)
Michael Messer, Stefan Albert, Solveig Plomer and Gaby Schneider
References
Michael Messer, Hendrik Backhaus, Albrecht Stroh and Gaby Schneider (2019+). Peak detection in times series
See Also
MFT.peaks, plot.MFT, summary.MFT, MFT.rate, MFT.variance, MFT.mean
Examples
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)