LinCheng Zhao

Publications (2)1.4 Total impact

• Article: Approximation by randomly weighting method in censored regression model

  ZhanFeng Wang, YaoHua Wu, LinCheng Zhao
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  ABSTRACT: Censored regression (“Tobit”) models have been in common use, and their linear hypothesis testings have been widely studied. However, the critical values of these tests are usually related to quantities of an unknown error distribution and estimators of nuisance parameters. In this paper, we propose a randomly weighting test statistic and take its conditional distribution as an approximation to null distribution of the test statistic. It is shown that, under both the null and local alternative hypotheses, conditionally asymptotic distribution of the randomly weighting test statistic is the same as the null distribution of the test statistic. Therefore, the critical values of the test statistic can be obtained by randomly weighting method without estimating the nuisance parameters. At the same time, we also achieve the weak consistency and asymptotic normality of the randomly weighting least absolute deviation estimate in censored regression model. Simulation studies illustrate that the performance of our proposed resampling test method is better than that of central chi-square distribution under the null hypothesis.
  Science in China Series A Mathematics 04/2012; 52(3):561-576. · 0.70 Impact Factor
• Source

  Available from: Guanqun Cao

  Article: Inference of change-point in single index models

  GuanQun Cao, ZhanFeng Wang, YaoHua Wu, LinCheng Zhao
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  ABSTRACT: Single index models are widely used in medicine, econometrics and some other fields. In this paper, we consider the inference of a change point problem in single index models. Based on density-weighted average derivative estimation (ADE) method, we propose a statistic to test whether a change point exists or not. The null distribution of the test statistic is obtained using a permutation technique. The permuted statistic is rigorously shown to have the same distribution in the limiting sense under both null and alternative hypotheses. After the null hypothesis of no change point is rejected, an ADE-based estimate of the change point is proposed under assumption that the change point is unique. A simulation study confirms the theoretical results.
  Science in China Series A Mathematics 04/2012; 51(10):1855-1870. · 0.70 Impact Factor