mistral-package {mistral} | R Documentation |
Provide tools for structural reliability analysis (failure probability, quantile).
Package: | mistral | |
Type: | Package | |
Version: | 2.1.0 Date: | 2016-04-03 |
License: | CeCILL |
This package provides tools for structural reliability analysis:
Calculate failure probability with FORM method and importance sampling,
Calculate failure probability with crude Monte Carlo method,
Calculate failure probability with Subset Simulation algorithm,
Calculate failure probability with Monotonic Reliability Methods (MRM),
Calculate failure probability with metamodel based algorithms : AKMCS, SMART and MetaIS,
Calculate failure probability with a metamodel based Subset Simulation : S2MART,
Wilks formula: Compute a quantile (or tolerance interval) with a given confidence level from a i.i.d. sample,
Wilks formula: Compute the minimal sample size to estimate a quantile with a given confidence level,
Calculate a quantile under monotonicity constraints.
Clement Walter, Gilles Defaux, Bertrand Iooss, Vincent Moutoussamy, with contributions from Nicolas Bousquet, Claire Cannamela and Paul Lemaitre (maintainer: Bertrand Iooss biooss@yahoo.fr)
O. Ditlevsen and H.O. Madsen. Structural reliability methods, Wiley, 1996.
M. Lemaire, A. Chateauneuf and J. Mitteau. Structural reliability, Wiley Online Library, 2009.
J. Morio and M. Balesdent. Estimation of rare event probabilities in complex aerospace and other systems, WP, 2016.
S.S. Wilks. Determination of Sample Sizes for Setting Tolerance Limits. Annals Mathematical Statistics, 12:91-96, 1941.
########## FORM ########### distribution = list() distribution[[1]] = list("gamma",c(2,1)) distribution[[2]] = list("gamma",c(3,1)) f <- function(X){ X[1]/sum(X) - qbeta((1e-5),2,3) } res <- FORM(f, u.dep = c(0,0.1), inputDist = distribution, N.calls = 1000, eps = 1e-7, Method = "HLRF", IS = "TRUE", q = 0.1, copula = "unif") ########### Wilks ########## N <- WilksFormula(0.95,0.95,order=1) print(N)