We consider n observations from the GARCH-type model:
S = σ2Z, where σ2 and Z are independent random variables. We develop
a new wavelet linear estimator of the unknown density of σ2 under
four different dependence structures: the strong mixing case, the β-
mixing case, the pairwise positive quadrant case and the ρ-mixing case.
Its asymptotic mean integrated squared error properties are explored.
In each case, we prove that it attains a fast rate of convergence.
Chesneau,C. and Doosti,H. (2022). Wavelet Linear Density Estimation for a GARCH Model under Various Dependence Structures. Journal of the Iranian Statistical Society, 11(1), 1-21.
MLA
Chesneau,C. , and Doosti,H. . "Wavelet Linear Density Estimation for a GARCH Model under Various Dependence Structures", Journal of the Iranian Statistical Society, 11, 1, 2022, 1-21.
HARVARD
Chesneau C., Doosti H. (2022). 'Wavelet Linear Density Estimation for a GARCH Model under Various Dependence Structures', Journal of the Iranian Statistical Society, 11(1), pp. 1-21.
CHICAGO
C. Chesneau and H. Doosti, "Wavelet Linear Density Estimation for a GARCH Model under Various Dependence Structures," Journal of the Iranian Statistical Society, 11 1 (2022): 1-21,
VANCOUVER
Chesneau C., Doosti H. Wavelet Linear Density Estimation for a GARCH Model under Various Dependence Structures. JIRSS, 2022; 11(1): 1-21.
Journal of the Iranian Statistical Society