  In this paper, we establish weak consistency and asymptotic normality of an
M-estimator of the regression function for left truncated and right censored
(LTRC) model, where it is assumed that the observations form a stationary
alpha-mixing sequence. The result holds with unbounded objective function, and
are applied to derive weak consistency and asymptotic normality of a kernel
classical regression curve estimate. We also obtain a uniform weak convergence
rate for the product-limit estimator of the lifetime and censored distribution
under dependence, which are useful results for our study and other LTRC strong
mixing framework. Some simulations are drawn to illustrate the results for
finite sample.
