MC_SubSam {TesiproV}

MonteCarlo with Subset-Sampling

Description

MonteCarlo with Subset-Sampling

Usage

MC_SubSam(
  lsf,
  lDistr,
  Nsubset = 1e+05,
  p0 = 0.1,
  MaxSubsets = 10,
  Alpha = 0.05,
  variance = "uniform",
  debug.level = 0
)

Arguments

lsf

limit-state function

lDistr

list of basevariables in input space

Nsubset

number of samples in each simulation level

p0

level probability or conditional probability

MaxSubsets

maximum number of simulation levels that are used to terminate the simulation procedure to avoid infinite loop when the target domain cannot be reached

Alpha

confidence level

variance

gaussian, uniform

debug.level

If 0 no additional info if 2 high output during calculation

Value

The results are provided within a list() of the following elements:

beta

pf

betaCI and pfCI are the corresponding confidence intervals

CoV COV of the result

NumOfSubsets Amount of Markov-Chains

NumOfEvalLSF_nom Markov-Chains times Iterations

NumOfEvalLSF_eff Internal counter that shows the real evaluations of the lsf

runtime Duration since start to finish of the function

Author(s)

(C) 2021 - K. Nille-Hauf, T. Feiri, M. Ricker - Hochschule Biberach, Institut fuer Konstruktiven Ingenieurbau

References

AU, S. K. & BECK, J. L. Estimation of small failure probabilities in high dimensions by subset simulation. Probabilistic Engineering Mechanics, 2001, 16.4: 263-277.