Self-Normalized Weak Invariance Principle for Mixing Sequences
AbstractIn this article we give a necessary and su±cient condition for a selfnormalized weak invariance principle, in the case of a strictly stationary Á-mixing sequence fXjgj¸1. This is obtained under the assumptions that the function L(x) = EX2 1 1fjX1·xg is slowly varying at 1 and the mixing coe±cients satisfy Á1=2(n)
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Bibliographic InfoPaper provided by Département des sciences administratives, UQO in its series RePAd Working Paper Series with number lrsp-TRS417.
Length: 15 pages
Date of creation: 30 Mar 2005
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Self-normalized; weak invariance principle; mixing sequences.;
Find related papers by JEL classification:
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
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- Shao, Qi-Man, 1993. "Almost sure invariance principles for mixing sequences of random variables," Stochastic Processes and their Applications, Elsevier, vol. 48(2), pages 319-334, November.
- Shao, Q. M., 1995. "Strong Approximation Theorems for Independent Random Variables and Their Applications," Journal of Multivariate Analysis, Elsevier, vol. 52(1), pages 107-130, January.
- Kulik, Rafal, 2006. "Limit theorems for self-normalized linear processes," Statistics & Probability Letters, Elsevier, vol. 76(18), pages 1947-1953, December.
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