Robust Range using Boxplot 'Quartiles'
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.
rrange(x, range=1, coef = 1.5, na.rm = TRUE)
x |
numeric vector the robust range of which shall be computed. |
range |
number for S compatibility; |
coef |
numeric multiplication factor definying the outlier boundary, see ‘Details’ below. |
na.rm |
logical indicating how |
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.
numeric vector c(m,M) with m <= M which is (not
strictly) inside range(x) = c(min(x),max(x)).
Martin Maechler, 1990.
range, fivenum,
boxplot and boxplot.stats.
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.
stopifnot(rrange(c(1:10,1000)) == c(1,10))
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