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completely new sequential importance sampling estimator of the desired tail probability. Numerical experiments suggest that the … sequential importance sampling estimator can be significantly more efficient than its competitor. …
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Logan et al. (1973) analyze the limit probability distribution of the statistic sn(p) = Σi=1 Xi/(Σi=1 Χj ) /p as n → ∞, when Xi is in the domain of attraciton of a stable law with stabilility index a. By simulations, we provide quantiles of the usual critical levels of the finite-sample...
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have approximately Exponential or Pareto tails, thanks to Extreme Value Theory. It is shown that a simple "robust …
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This paper provides a new approach to recover relative entropy measures of contemporaneous dependence from limited information by constructing the most entropic copula (MEC) and its canonical form, namely the most entropic canonical copula (MECC). The MECC can effectively be obtained by...
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importance sampling or the independence chain Metropolis-Hastings algorithm for posterior analysis. A comparative analysis is … appropriately yet quickly tuned candidate, straightforward importance sampling provides the most efficient estimator of the marginal …
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