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

integer: Number of observations to be generated

method

character: Particular method to be used for random number generation.

relativeTolerance

numeric: the relative tolerance level of deviation of the generated confidence interval from the specified interval. If this deviation is greater than relativeTolerance a warning is given.

...

Optional arguments to be passed to the particular random number generating function.

Methods (by class)

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"]])

[Package decisionSupport version 1.114 Index]