Dear R-List-Member,
is there a more elegant way to obtain p-values of a vector x, whose
empirical density has been estimated with density(), than summing up the
rectangles as an approximation of the area beneath the empirical
distribution function and interpolating the values of x by using approx()?
pval.emp <- function(x)
{
df <- density(x,from=min(x),to=max(x),kernel="gaussian")
width <- df$x[2]-df$x[1]
rect <- df$y*width
cdf.emp <- cumsum(rect)
approx(df$x,cdf.emp,x)$y
}
Many thks in advance,
Bernhard
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