A goodness-of-fit test for exchangeable Archimedean copulas is presented. In a large-scale simulation study it is shown that the test performs well according to the error probability of the first kind and the power under several alternatives, especially in large dimensions. The proposed test is compared to other known tests for Archimedean copulas. In contrast to the latter, the former is simpl...

random number generation is one of the human abilities. it is proven that the sequence of random numbers generated by people do not follow full randomness criteria. these numbers produced by brain activity seem to be completely non stationary. in this paper, we show that there is a distinction between the random numbers generated by different people who provides the discrimination capability, a...

We propose an Iterative Nonlinear Gaussianization Algorithm (INGA) which seeks a nonlinear map from a set of dependent random variables to independent Gaussian random variables. A direct motivation of INGA is to extend principal component analysis (PCA), which transforms a set of correlated random variables into uncorrelated (independent up to second order) random variables, and Independent Com...

We develop sampling algorithms for multivariate Archimedean copulas. For exchangeable copulas, where there is only one generating function, we first analyse the distribution of the copula itself, deriving a number of integral representations and a generating function representation. One of the integral representations is related, by a form of convolution, to the distribution whose Laplace trans...

Applications in operations research often employ models which contain linear functions. These linear functions may have some components (coefficients and variables) which are random. (For instance, linear functions in mathematical programming often represent models of processes which exhibit randomness in resource availability, consumption rates, and activity levels.) Even when the linearity as...

Markov chain Monte Carlo (MCMC) routines have become a fundamental means for generating random variates from distributions otherwise difficult to sample. The Hastings sampler, which includes the Gibbs and Metropolis samplers as special cases, is the most popular MCMC method. A number of implementations are available for running these MCMC routines varying in the order through which the componen...

Let X1,X2, ... be independent and symmetric random variables such that Sn = X1+ ...+Xn converges to a finite valued random variable S a.s. and let S = sup1≤n<∞ Sn (which is finite a.s.). We construct upper and lower bounds for sy and s ∗ y, the upper 1 y th quantile of Sy and S , respectively. Our approximations rely on an explicitly computable quantity q y for which we prove that 1 2 q y/2 < s...

The CV-S method is a high-efficiency random sampling to estimate statistical moments of variables, and it uses an approximated target parameter which are linearly dependent on input as mockup parameter. In order enhance the applicability method, we propose use different from but similar whose sensitivity coefficients available. present work, nuclear fuel burnup problems concerned, standard devi...

Variance reduction techniques have been shown by others in the past to be a useful tool to reduce variance in Simulation studies. However, their application and success in the past has been mainly domain specific, with relatively little guidelines as to their general applicability, in particular for novices in this area. To facilitate their use, this study aims to investigate the robustness of ...