Qiu, Jin Two stage estimator in semiparametric model under random censorship. (Chinese. English summary) Zbl 0911.62033 Appl. Math., Ser. A (Chin. Ed.) 13, No. 3, 281-288 (1998). Summary: Consider the semiparametric regression model \(y_i= x_i'\beta+ g(t_i)+e_i\), \(1\leq i\leq n\), \(g\) is an unknown function on \(R^1\), \(\beta\) is a \(p\times 1\) parametric vector to be estimated and \(e_i\) is an unobserved random error. When \(y_i\) is randomly censored, on the basis of the additivity of the model, the author obtains a two stage estimator of \(\beta\) and a kernel estimator of \(g\) by using the synthetic data method. The strong consistency of these two estimators is proved. MSC: 62G07 Density estimation 62F10 Point estimation 62H12 Estimation in multivariate analysis Keywords:additive regression model; ordinary least squares; semiparametric regression; kernel estimator; synthetic data PDFBibTeX XMLCite \textit{J. Qiu}, Appl. Math., Ser. A (Chin. Ed.) 13, No. 3, 281--288 (1998; Zbl 0911.62033)