uq | R Documentation |
Evaluates quantile of distribution approximately using
a unuran
object that implements an inversion method.
[Universal] – Quantile Function.
uq(unr, U)
unr |
a |
U |
vector of probabilities. |
The routine evaluates the quantiles (inverse CDF) for a given
(vector of) probabilities approximately.
It requires a unuran
object that implements an inversion method.
Currently these are
‘HINV’
‘NINV’
‘PINV’
for continuous distributions and
‘DGT’
for discrete distributions.
uq
returns the left boundary of the domain of the distribution
if argument U
is less than or equal to 0
and
the right boundary if U
is greater than or equal to 1
.
Josef Leydold and Wolfgang H\"ormann unuran@statmath.wu.ac.at.
W. H\"ormann, J. Leydold, and G. Derflinger (2004): Automatic Nonuniform Random Variate Generation. Springer-Verlag, Berlin Heidelberg.
unuran
,unuran.new
.
## Compute quantiles of normal distribution using method 'PINV' gen <- pinv.new(pdf=dnorm, lb=-Inf, ub=Inf) uq(gen,seq(0,1,0.05)) ## Compute quantiles of user-defined distribution using method 'PINV' pdf <- function (x) { exp(-x) } gen <- pinv.new(pdf=pdf, lb=0, ub=Inf, uresolution=1.e-12) uq(gen,seq(0,1,0.05)) ## Compute quantiles of binomial distribution using method 'DGT' gen <- dgt.new(pv=dbinom(0:1000,1000,0.4), from=0) uq(gen,seq(0,1,0.05)) ## Compute quantiles of normal distribution using method 'HINV' ## (using 'advanced' interface) gen <- unuran.new("normal()","hinv") uq(gen,0.975) uq(gen,c(0.025,0.975)) ## Compute quantiles of user-defined distributio using method 'HINV' ## (using 'advanced' interface) cdf <- function (x) { 1.-exp(-x) } pdf <- function (x) { exp(-x) } dist <- new("unuran.cont", cdf=cdf, pdf=pdf, lb=0, ub=Inf) gen <- unuran.new(dist, "hinv; u_resolution=1.e-12") uq(gen,seq(0,1,0.05))
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