In this talk, we will discuss about a nonparametric estimator of the regression function based
on the local linear method when the loss function is the mean squared relative error and the data left truncated.
The proposed method avoids the problem of boundary effects and reduces the bias term in addition to being
robust against the presence of outliers. Under suitable assumptions, the estimator’s strong uniform
almost sure consistency with rate is established and its finite-sample properties are investigated
by means of a simulation study.