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On sample marginal quantiles for stationary processes

  • Dominicy, Yves
  • Hörmann, Siegfried
  • Ogata, Hiroaki
  • Veredas, David

We establish the asymptotic normality of marginal sample quantiles for S-mixing vector stationary processes. S-mixing is a recently introduced and widely applicable notion of dependence. Results of some Monte Carlo simulations are given.

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Article provided by Elsevier in its journal Statistics & Probability Letters.

Volume (Year): 83 (2013)
Issue (Month): 1 ()
Pages: 28-36

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Handle: RePEc:eee:stapro:v:83:y:2013:i:1:p:28-36
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  1. Oberhofer, Walter & Haupt, Harry, 2005. "The asymptotic distribution of the unconditional quantile estimator under dependence," Statistics & Probability Letters, Elsevier, vol. 73(3), pages 243-250, July.
  2. Berkes, István & Hörmann, Siegfried & Schauer, Johannes, 2009. "Asymptotic results for the empirical process of stationary sequences," Stochastic Processes and their Applications, Elsevier, vol. 119(4), pages 1298-1324, April.
  3. Dutta, Kalyan & Sen, Pranab Kumar, 1971. "On the Bahadur representation of sample quantiles in some stationary multivariate autoregressive processes," Journal of Multivariate Analysis, Elsevier, vol. 1(2), pages 186-198, June.
  4. Sen, Pranab Kumar, 1972. "On the Bahadur representation of sample quantiles for sequences of [phi]-mixing random variables," Journal of Multivariate Analysis, Elsevier, vol. 2(1), pages 77-95, March.
  5. Jean-David FERMANIAN & Olivier SCAILLET, 2003. "Nonparametric Estimation of Copulas for Time Series," FAME Research Paper Series rp57, International Center for Financial Asset Management and Engineering.
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