Wavelet estimation of a regression model with mixed noises

Chesneau et al. ( Journal of Computational and Applied Mathematics , 2020) study nonparametric wavelet estimations over L 2 risk of a regression model with additive and multiplicative noises. This paper considers convergence rates over L p ( 1 ≤ p < + ∞ ) risk of linear wavelet estimator and nonlinear wavelet estimator under some mild conditions. It turns out that our results reduce to the theorems of Chesneau et al., when p = 2 .