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spup (version 1.2-1)

genSample.JointScalar: Generating sample from cross-correlated variables described by a scalar.

Description

Generating sample from cross-correlated variables described by a scalar.

Usage

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

Arguments

UMobject

object of a class JointScalar created using defineMUM.R

n

integer; number of Monte Carlo runs

samplemethod

"randomSampling" or "lhs".

p

a vector of quantiles. Optional. Only required if sample method is "lhs".

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

Monte Carlo sample of cross-correlated scalar variables.

Examples

Run this code
# NOT RUN {
set.seed(12345)
scalarUM <- defineUM(uncertain = TRUE, distribution = "norm",
                     distr_param = c(1, 2), id="Var1")                
scalarUM2 <- defineUM(uncertain = TRUE, distribution = "norm",
                      distr_param = c(3, 2), id="Var2")
scalarUM3 <- defineUM(uncertain = TRUE, distribution = "norm",
                      distr_param = c(10, 2.5), id="Var3")                
myMUM <- defineMUM(UMlist = list(scalarUM, scalarUM2, scalarUM3), 
               matrix(c(1,0.7,0.2,0.7,1,0.5,0.2,0.5,1), nrow = 3, ncol = 3))
my_sample <- genSample(myMUM, n = 10, samplemethod = "randomSampling", asList = FALSE)
my_sample  

# }

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