Estimation in nonparametric regression model with additive and multiplicative noise via Laguerre series

We look into the nonparametric regression estimation with additive and multiplicative noise construct adaptive thresholding estimators based on Laguerre series. The proposed approach achieves asymptotically near-optimal convergence rates when unknown function belongs to Laguerre–Sobolev space. consider problem under two structures; (1) i.i.d. Gaussian errors (2) long-memory errors. In case, our are similar those found in literature. depend parameters only is strong enough either source, otherwise, identical noise.