Description Usage Arguments Value Author(s) See Also Examples
Identifies and drops outliers within a singlecase data frame (scdf).
1 
data 
A singlecase data frame. See 
criteria 
Specifies the criteria for outlier identification. Set

data 
A data frame (for each singlecase) without outliers. 
dropped.n 
A list with the number of dropped data points for each singlecase. 
dropped.mt 
A list with the measurementtimes of dropped
data points for each singlecase (values are based on the 
sd.matrix 
A list with a matrix for each case with values for the upper and lower boundaries based on the standard deviation. 
ci.matrix 
A list with a matrix for each singlecase with values for the upper and lower boundaries based on the confidence interval. 
cook 
A list of Cook's Distances for each measurement of each singlecase. 
criteria 
Criteria used for outlier analysis. 
N 
Number of singlecases. 
case.names 
Case identifier. 
Juergen Wilbert
describeSC
, fillmissingSC
,
plotSC
1 2 3 4 5 6 7 8 9  ## Identify outliers using 1.5 standard deviations as criterion
susanne < rSC(level = 1.0)
res < outlierSC(susanne, criteria = c("SD", 1.5))
plotSC(susanne, marks = list(positions = res$dropped.mt))
## Identify outliers in the original data from Grosche (2011) using Cook's Distance
## greater than 4/n as criterion
res < outlierSC(Grosche2011, criteria = c("Cook", "4/n"))
plotSC(Grosche2011, marks = list(positions = res$dropped.mt))

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