quinterpol: Interpolated Quantiles
In regr0: Building regression models

Description Usage Arguments Details Value Author(s) See Also Examples

This function implements a version of empirical quantiles based on interpolation

1	quinterpol(x, probs = c(0.25, 0.5, 0.75), extend = TRUE)

`x`	vector of data determining the quantiles
`probs`	vector of probabilities defining which quantiles should be produced
`extend`	logical: Should quantiled be calculated outside the range of the data by linear extrapolation?

The empirical quantile function jumps at the data values according to the usual definition. The version of quantiles calculated by 'quinterpol' avoids jumps. It is based on linear interpolation of the step version of the empirical cumulative distribution function, using as the given points the midpoints of both vertical and horizontal pieces of the latter. See 'examples' for a visualization.

vector of quantiles

Werner A. Stahel

quantile

## This example illustrates the definition of the "interpolated quantiles"

set.seed(2)
t.x <- sort(round(2*rchisq(20,2)))
table(t.x)
t.p <- ppoints(100)
plot(quinterpol(t.x,t.p),t.p, type="l")