there are several theorical results about order statistics and copulas in the literature that have  been mentioned also by nelsen cite{p20}. the present study after reviewing some of these results, relies on  simulation technique to investigate the mentioned results about order statistics and copulas. the study concentrates on two well known archimedean gumbel and frank families in the case tha...

Many of the methods in computational statistics require the ability to generate random variables from known probability distributions. This is at the heart of Monte Carlo simulation for statistical inference (Chapter 6), bootstrap and resampling methods (Chapters 6 and 7), Markov chain Monte Carlo techniques (Chapter 11), and the analysis of spatial point processes (Chapter 12). In addition, we...

Many quantitative problems in science, engineering, and economics are nowadays solved via statistical sampling on a computer. Such Monte Carlo methods can be used in three different ways: (1) to generate random objects and processes in order to observe their behavior, (2) to estimate numerical quantities by repeated sampling, and (3) to solve complicated optimization problems through randomized...