Local polynomial quasi-likelihood regression with truncated and dependent data

摘要

The local polynomial quasi-likelihood estimation has several good statistical properties such as high mini-max efficiency and adaptation of edge effects. In this paper, we construct a local quasi-likelihood regression estimator for a left truncated model, and establish the asymptotic normality of the proposed estimator when the observations form a stationary and α-mixing sequence, such that the corresponding result of Fan et al. [Local polynomial kernel regression for generalized linear models and quasilikelihoodfunctions, J. Amer. Statist. Assoc. 90 (1995), pp. 141 -150] is extended from the i ndependent and complete data to the dependent and truncated one. Finite sample behaviour of the estimator is investigated via simulations too.