Evaluates quantile of distribution approximately using a unuran object that implements an inversion method.
[Universal] -- Quantile Function.
uq(unr, U)
Arguments
unr: a unuran object that implements an inversion menthod.
U: vector of probabilities.
Details
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 0and the right boundary if U is greater than or equal to 1.
See Also
unuran,unuran.new.
References
W. H"ormann, J. Leydold, and G. Derflinger (2004): Automatic Nonuniform Random Variate Generation. Springer-Verlag, Berlin Heidelberg.
## 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))