| quantile {stats} | R Documentation |
The generic function quantile produces sample quantiles
corresponding to the given probabilities.
The smallest observation corresponds to a probability of 0 and the
largest to a probability of 1.
quantile(x, ...)
## Default S3 method:
quantile(x, probs = seq(0, 1, 0.25), na.rm = FALSE,
names = TRUE, ...)
x |
numeric vectors whose sample quantiles are wanted. |
probs |
numeric vector with values in [0,1]. |
na.rm |
logical; if true, any NA and NaN's
are removed from x before the quantiles are computed. |
names |
logical; if true, the result has a names
attribute. Set to FALSE for speedup with many probs. |
... |
further arguments passed to or from other methods. |
A vector of length length(probs) is returned;
if names = TRUE, it has a names attribute.
quantile(x,p) as a function of p linearly interpolates
the points ( (i-1)/(n-1), ox[i] ), where
ox <- sort(x) and n <- length(x).
This gives quantile(x, p) == (1-f)*ox[i] + f*ox[i+1], where
r <- 1 + (n-1)*p, i <- floor(r), f <- r - i
and ox[n+1] := ox[n].
NA and NaN values in probs are
propagated to the result.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
ecdf (in the stats package) for
empirical distributions of which quantile is the
“inverse”;
boxplot.stats and fivenum for computing
“versions” of quartiles, etc.
quantile(x <- rnorm(1001))# Extremes & Quartiles by default quantile(x, probs=c(.1,.5,1,2,5,10,50, NA)/100)