On regression representations of stochastic processes
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Cited by:
- Alfred Müller & Marco Scarsini, 2001.
"Stochastic Comparison of Random Vectors with a Common Copula,"
Mathematics of Operations Research, INFORMS, vol. 26(4), pages 723-740, November.
- Marco Scarsini & Alfred Muller, 2001. "Stochastic comparison of random vectors with a common copula," Post-Print hal-00540198, HAL.
- Lamboni, Matieyendou, 2022. "Efficient dependency models: Simulating dependent random variables," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 200(C), pages 199-217.
- Mai Jan-Frederik & Schenk Steffen & Scherer Matthias, 2015. "Analyzing model robustness via a distortion of the stochastic root: A Dirichlet prior approach," Statistics & Risk Modeling, De Gruyter, vol. 32(3-4), pages 177-195, December.
- Alessio Sancetta, 2007. "Weak Convergence of Laws on ℝ K with Common Marginals," Journal of Theoretical Probability, Springer, vol. 20(2), pages 371-380, June.
- Sancetta, Alessio, 2005. "Distance between nonidentically weakly dependent random vectors and Gaussian random vectors under the bounded Lipschitz metric," Statistics & Probability Letters, Elsevier, vol. 75(3), pages 158-168, December.
- Sancetta, Alessio, 2007. "Nonparametric estimation of distributions with given marginals via Bernstein-Kantorovich polynomials: L1 and pointwise convergence theory," Journal of Multivariate Analysis, Elsevier, vol. 98(7), pages 1376-1390, August.
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Keywords
representation as function of i.i.d. sequences * generalized two-block factor * m-dependence * Markov regression * Markov chain;Statistics
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