Quantiles of Weighted Empirical Cumulative Distribution Function
Compute quantiles of a weighted empirical cumulative distribution function.
## S3 method for class 'ewcdf'
quantile(x, probs = seq(0, 1, 0.25),
names = TRUE, ...,
normalise = TRUE, type=1)x |
A weighted empirical cumulative distribution function
(object of class |
probs |
probabilities for which the quantiles are desired. A numeric vector of values between 0 and 1. |
names |
Logical. If |
... |
Ignored. |
normalise |
Logical value indicating whether |
type |
Integer specifying the type of quantile to be calculated,
as explained in |
This is a method for the generic quantile
function for the class ewcdf of empirical weighted cumulative
distribution functions.
The quantile for a probability p is computed
as the right-continuous inverse of the cumulative
distribution function x (assuming type=1, the default).
If normalise=TRUE (the default),
the weighted cumulative function x is first normalised to
have total mass 1 so that it can be interpreted as a
cumulative probability distribution function.
Numeric vector of quantiles, of the same length as probs.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk and Kevin Ummel.
z <- rnorm(50) w <- runif(50) Fun <- ewcdf(z, w) quantile(Fun, c(0.95,0.99))
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