spup (version 1.2-1)

genSample.MarginalScalar: Generating Monte Carlo sample from an uncertain object of a class 'MarginalScalar'

Description

Function that runs Monte Carlo simulations for MarginalScalar class objects.

Usage

# S3 method for MarginalScalar
genSample(UMobject, n, samplemethod, p = 0,
  asList = TRUE, ...)

Arguments

UMobject

uncertain object defined using defineUM().

n

Integer. Number of Monte Carlo realizations.

samplemethod

"randomSampling" or "stratifiedSampling".

p

A vector of quantiles. Optional. Only required if sample method is "stratifiedSampling".

asList

logical. If asList = TRUE returns list of all samples as a list. If asList = FALSE returns samples in a format of distribution parameters in UMobject.

...

Additional parameters.

Value

A Monte Carlo sample of uncertain input of a class of distribution parameters.

Details

"stratifiedSampling" Number of samples (n) must be dividable by the number of quantiles to assure each quantile is evenly represented.

Examples

# NOT RUN {
set.seed(12345)
# Example 1
scalarUM <- defineUM(uncertain = TRUE, distribution = "norm", distr_param = c(10, 1))
scalar_sample <- genSample(scalarUM, n = 10, samplemethod = "randomSampling")

# Example 2
scalarUM <- defineUM(uncertain = TRUE, distribution = "beta", distr_param = c(10, 1, 2))
scalar_sample <- genSample(scalarUM, n = 10, samplemethod = "stratifiedSampling", p = 0:5/5)

# }