binMeas: "Smooth, de-trend, and binarise the measurement"
In dmattek/ARCOS: Automatic Recognition of Collective Signalling

binMeas

R Documentation

"Smooth, de-trend, and binarise the measurement"

Description

First a short-term median filter with size smoothK is applied to remove fast noise from the time series. If the de-trending method is set to "none", smoothing is applied on globally rescaled time series. The subsequent de-trending can be performed with a long-term median filter with the size biasK (biasMet = "runmed") or by fitting a polynomial of degree polyDeg (biasMet = "lm").

After de-trending, if the global difference between min/max is greater than the threshold peakThr the signal is rescaled to the [0,1] range.

The final signal is binarised using the binThr threshold. .

Usage

binMeas(
  obj,
  smoothK = 3L,
  biasK = 51L,
  peakThr = 0.2,
  polyDeg = 1L,
  biasMet = c("runmed", "lm", "none"),
  binThr = 0.5
)

## S3 method for class 'arcosTS'
binMeas(
  obj,
  smoothK = 3L,
  biasK = 51L,
  peakThr = 0.2,
  polyDeg = 1L,
  biasMet = c("runmed", "lm", "none"),
  binThr = 0.5
)

Arguments

`obj`	an arcosTS object.
`smoothK`	an integer, length of the short-term median filter, i.e. smoothing, default 3L.
`biasK`	an integer, length of the long-term median filter, i.e. de-trending, default 51L.
`peakThr`	a double, threshold for peak detection from signal rescaled to [0,1], default 0.2.
`polyDeg`	an integer, sets the degree of the polynomial for lm fitting; default 1.
`biasMet`	method for de-trending, choose from runmed (median filter), lm (linear regression), none, default runmed.
`binThr`	a double, threshold for signal binarisation, default 0.5.