Runuran.special.generators function

Generators for distributions based on methods from the UNU.RAN library

Generators for particular distributions. Their syntax is similar to the corresponding built-in functions.

Details

Runuran provides an interface to the UNU.RAN library for universal non-uniform random number generators. This is a very flexible and powerful collection of sampling routines, where the user first has to specify the target distribution and then has to choose an appropriate sampling method. However, we found that this approach is a little bit confusing for the beginner.

Thus we have prepared easy-to-use sampling functions for standard distributions to facilitate the use of the package. All these functions share a similar syntax and naming scheme (only u is prefixed) with their analogous

built-in generating functions (if these exist) but have optional domain arguments lb and ub, i.e., these calls also allow to draw samples from truncated distributions:

ur...(n, distribution parameters, lb , ub)

These functions also show the interested user how we used the more powerful functions. We recommend to directly use these more flexible functions. Then one has faster marginal generation times and one may choose the best generation method for one's application.

Currently generators for the following distributions are implemented.

Continuous Univariate Distributions (24):

Function		Distribution
urbeta		Beta
urburr		Burr
urcauchy		Cauchy
urchi		Chi
urchisq		Chi-squared
urexp		Exponential
urextremeI		Gumbel (extreme value type I)
urextremeII		Frechet (extreme value type II)
urf		F
urgamma		Gamma
urgig		GIG (generalized inverse Gaussian)
urhyperbolic		Hyperbolic
urlaplace		Laplace
urlnorm		Log-Normal
urlogis		Logistic
urlomax		Lomax
urnorm		Normal (Gaussian)
urpareto		Pareto (of first kind)
urplanck		Planck
urpowerexp		Powerexponential (Subbotin)
urrayleigh		Rayleigh
urt		t (Student)
urtriang		Triangular
urweibull		Weibull

Discrete Distributions (6):

Function		Distribution
urbinom		Binomial
urgeom		Geometric
urhyper		Hypergeometric
urlogarithmic		Logarithmic
urnbinom		Negative Binomial
urpois		Poisson

Author(s)

Josef Leydold and Wolfgang H"ormann unuran@statmath.wu.ac.at .

See Also

Runuran-package, Runuran.distributions.

Examples

## draw a sample of size 100 from a
## gamma distribution with shape parameter 5
x <- urgamma(n=100, shape=5)

## draw a sample of size 100 from a
## half normal distribution
x <- urnorm(n=100, lb=0, ub=Inf)