random {decisionSupport} | R Documentation |
Quantiles or empirically based generic random number generation.
Description
These functions generate random numbers for parametric distributions, parameters of which are determined by given quantiles or for distributions purely defined empirically.
Usage
random(rho, n, method, relativeTolerance, ...)
## Default S3 method:
random(
rho = list(distribution = "norm", probabilities = c(0.05, 0.95), quantiles =
c(-qnorm(0.95), qnorm(0.95))),
n,
method = "fit",
relativeTolerance = 0.05,
...
)
## S3 method for class 'vector'
random(rho = runif(n = n), n, method = NULL, relativeTolerance = NULL, ...)
## S3 method for class 'data.frame'
random(
rho = data.frame(uniform = runif(n = n)),
n,
method = NULL,
relativeTolerance = NULL,
...
)
Arguments
rho |
Distribution to be randomly sampled. |
n |
|
method |
|
relativeTolerance |
|
... |
Optional arguments to be passed to the particular random number generating function. |
Methods (by class)
-
random(default)
: Quantiles based univariate random number generation.- Arguments
-
rho
-
rho
list
: Distribution to be randomly sampled. The list elements are$distribution
,$probabilities
and$quantiles
. For details cf. below. method
-
character
: Particular method to be used for random number generation. Currently only methodrdistq_fit{fit}
is implemented which is the default. relativeTolerance
-
numeric
: the relative tolerance level of deviation of the generated confidence interval from the specified interval. If this deviation is greater thanrelativeTolerance
a warning is given. ...
-
Optional arguments to be passed to the particular random number generating function, i.e.
rdistq_fit
.
- Details
-
The distribution family is determined by
rho[["distribution"]]
. For the possibilities cf.rdistq_fit
.rho[["probabilities"]]
and[[rho"quantiles"]]
are numeric vectors of the same length. The first defines the probabilities of the quantiles, the second defines the quantiles values which determine the parametric distribution. - Value
-
A numeric vector of length
n
containing the generated random numbers. - See Also
-
random(vector)
: Univariate random number generation by drawing from a given empirical sample.- Arguments
-
rho
-
vector
: Univariate empirical sample to be sampled from. method
-
for this class no impact
relativeTolerance
-
for this class no impact
...
-
for this class no impact
- Value
-
A
numeric vector
of lengthn
containing the generated random numbers. - See Also
-
random(data.frame)
: Multivariate random number generation by drawing from a given empirical sample.- Arguments
-
rho
-
data.frame
: Multivariate empirical sample to be sampled from. method
-
for this class no impact
relativeTolerance
-
for this class no impact
...
-
for this class no impact
- Value
-
A
data.frame
withn
rows containing the generated random numbers. - See Also
Examples
x<-random(n=10000)
hist(x,breaks=100)
mean(x)
sd(x)
rho<-list(distribution="norm",
probabilities=c(0.05,0.4,0.8),
quantiles=c(-4, 20, 100))
x<-random(rho=rho, n=10000, tolConv=0.01)
hist(x,breaks=100)
quantile(x,p=rho[["probabilities"]])