Compute a robust range, i.e. the usual range() as long
as there are no outliers, using the whisker boundaries of
boxplot, i.e., boxplot.stats.
Usage
rrange(x, range=1, coef = 1.5, na.rm = TRUE)
Arguments
x
numeric vector the robust range of which shall be computed.
range
number for S compatibility; 1.5 * range is
equivalent to coef.
coef
numeric multiplication factor definying the outlier
boundary, see Details below.
na.rm
logical indicating how NA values should be
handled; they are simply dropped when na.rm = TRUE as by default.
Value
numeric vector c(m,M) with $m \le M$ which is (not
strictly) inside range(x) = c(min(x),max(x)).
Details
The robust range is really just what boxplot.stats(x,
coef=coef) returns as the whisker boundaries.
This is the most extreme values x[j] still inside median
plus/minus coef * IQR.
A more sophisticated robust range for (strongly) asymmetric data can
be derived from the skewness adjusted boxplot statistics
adjboxStats which is a generalization of
boxplot.stats.