Compute quantiles of a weighted empirical cumulative distribution function.
# S3 method for ewcdf
quantile(x, probs = seq(0, 1, 0.25),
names = TRUE, ...,
normalise = TRUE, type=1)
Numeric vector of quantiles, of the same length as probs
.
A weighted empirical cumulative distribution function
(object of class "ewcdf"
, produced by ewcdf
)
for which the quantiles are desired.
probabilities for which the quantiles are desired. A numeric vector of values between 0 and 1.
Logical. If TRUE
, the resulting vector of quantiles is
annotated with names corresponding to probs
.
Ignored.
Logical value indicating whether x
should first be normalised
so that it ranges between 0 and 1.
Integer specifying the type of quantile to be calculated,
as explained in quantile.default
.
Only types 1 and 2 are currently implemented.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk and Kevin Ummel.
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.
ewcdf
,
quantile
z <- rnorm(50)
w <- runif(50)
Fun <- ewcdf(z, w)
quantile(Fun, c(0.95,0.99))
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