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Quasi-random numbers for copula models. (English) Zbl 06737713
Summary: The present work addresses the question how sampling algorithms for commonly applied copula models can be adapted to account for quasi-random numbers. Besides sampling methods such as the conditional distribution method (based on a one-to-one transformation), it is also shown that typically faster sampling methods (based on stochastic representations) can be used to improve upon classical Monte Carlo methods when pseudo-random number generators are replaced by quasi-random number generators. This opens the door to quasi-random numbers for models well beyond independent margins or the multivariate normal distribution. Detailed examples (in the context of finance and insurance), illustrations and simulations are given and software has been developed and provided in the R packages copula and qrng.

##### MSC:
 62H99 Multivariate analysis 65C60 Computational problems in statistics (MSC2010)
##### Software:
Algorithm 823; nacopula; QRM
Full Text:
##### References:
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