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In Monte Carlo simulation, Latin hypercube sampling (LHS) [McKay et al. (1979)] is a well-known variance reduction technique for vectors of independent random variables. The method presented here, Latin hypercube sampling with dependence (LHSD), extends LHS to vectors of dependent random...
Persistent link: https://www.econbiz.de/10010301705
In Monte Carlo simulation, Latin hypercube sampling (LHS) [McKay et al. (1979)] is a well-known variance reduction technique for vectors of independent random variables. The method presented here, Latin hypercube sampling with dependence (LHSD), extends LHS to vectors of dependent random...
Persistent link: https://www.econbiz.de/10009277829
We consider the problem of reducing the variance of Monte Carlo estimators of multivariate estimation problems by combining the variance reduction techniques Latin hypercube sampling with dependence (LHSD), control variates and importance sampling. Under some standard conditions, the resulting...
Persistent link: https://www.econbiz.de/10013097629
Persistent link: https://www.econbiz.de/10003971915
Persistent link: https://www.econbiz.de/10003759970
In Monte Carlo simulation, Latin hypercube sampling (LHS) [McKay et al. (1979)] is a well-known variance reduction technique for vectors of independent random variables. The method presented here, Latin hypercube sampling with dependence (LHSD), extends LHS to vectors of dependent random...
Persistent link: https://www.econbiz.de/10011293923