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Information Journal Paper

Title

WAVELET LINEAR DENSITY ESTIMATION FOR A GARCH MODEL UNDER VARIOUS DEPENDENCE STRUCTURES

Pages

  1-21

Abstract

 We consider n observations from the GARCH-type model: S = s2 Z, where s2 and Z are independent random variables. We develop a new wavelet LINEAR ESTIMATOR of the unknown density of s2 under four different dependence structures: the strong mixing case, the b-mixing case, the pairwise positive quadrant case and the r-mixing case. Its asymptotic mean integrated squared error properties are explored. In each case, we prove that it attains a fast RATE OF CONVERGENCE.

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    APA: Copy

    CHESNEAU, CHRISTOPHE, & DOOSTI, HASSAN. (2012). WAVELET LINEAR DENSITY ESTIMATION FOR A GARCH MODEL UNDER VARIOUS DEPENDENCE STRUCTURES. JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS), 11(1), 1-21. SID. https://sid.ir/paper/117858/en

    Vancouver: Copy

    CHESNEAU CHRISTOPHE, DOOSTI HASSAN. WAVELET LINEAR DENSITY ESTIMATION FOR A GARCH MODEL UNDER VARIOUS DEPENDENCE STRUCTURES. JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS)[Internet]. 2012;11(1):1-21. Available from: https://sid.ir/paper/117858/en

    IEEE: Copy

    CHRISTOPHE CHESNEAU, and HASSAN DOOSTI, “WAVELET LINEAR DENSITY ESTIMATION FOR A GARCH MODEL UNDER VARIOUS DEPENDENCE STRUCTURES,” JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS), vol. 11, no. 1, pp. 1–21, 2012, [Online]. Available: https://sid.ir/paper/117858/en

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