MEAsmooth {rMEA} | R Documentation |
Moving average smoothing for motion energy data
Description
This function applies a moving average filter, based on SAS "proc expand" procedure. The moving average is applied independently on each subject's motion energy data. NA values are set to 0.
Usage
MEAsmooth(mea, moving.average.win = 0.5)
Arguments
mea |
an object of class |
moving.average.win |
numeric. The size of the filter window, in seconds or fractions of seconds. |
Value
The filtered object(s)
Examples
## read the first 4 minutes of the normal sample
## (intake interviews of patients that carried on therapy)
path_normal <- system.file("extdata/normal", package = "rMEA")
mea_raw <- readMEA(path_normal, sampRate = 25, s1Col = 1, s2Col = 2,
s1Name = "Patient", s2Name = "Therapist",
idOrder = c("id","session"), idSep="_", skip=1, nrow = 6000)
## filter with moving average
mea_filter = MEAsmooth(mea_raw)
## assign groups names
mea_raw <- setGroup(mea_raw, "raw")
mea_filter <- setGroup(mea_filter, "filtered")
## Compute ccf
mea_raw <- MEAccf(mea_raw, lagSec = 5, winSec = 60, incSec = 30, r2Z = TRUE, ABS = FALSE)
mea_filter <- MEAccf(mea_filter, lagSec = 5, winSec = 60, incSec = 30, r2Z = TRUE, ABS = FALSE)
## Compare the effect of filtering on ccf
MEAlagplot(mea_filter, contrast = mea_raw)
[Package rMEA version 1.2.2 Index]