Asymptotic properties for the estimators in heteroscedastic semiparametric EV models with α-mixing errors

Statistical Inference for Estimators in a Semiparametric EV Model with Linear Process Errors and Missing Responses

“…Under the condition of complete data, the research on a semiparametric regression model and a semiparametric EV model has obtained many ideal results. For example, Jiang [11] proposed an average least squares estimator for an unknown parameter β and discussed the properties of the new estimator; Wu [12] proposed a ridge-type estimator for the unknown parameter in a semiparametric EV model with linear measurement errors; Xi et al [13] proved the asymptotic properties for the estimators of β, g(•), and f(•) based on α-mixing random errors; Cui and Li [14] presented the asymptotic distributions for estimators of β, g(•), and error variance; Zhou et al [15] considered estimation and inference procedures for a fxed-efects model. It should be noted that most of the studies on semiparametric regression models are discussed in the context of complete data.…”