Riquan Zhang

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Varying coefficient error-in-covariables models are considered with surrogate data and validation sampling. Without specifying any error structure equation, two estimators for the coefficient function vector are suggested by using the local linear kernel smoothing technique. The proposed estimators are proved to be asymptotically normal. A bootstrap(More)
Abstract Semivarying coefficient models are frequently used in statistical models. In this paper, under the condition that the coefficient functions possess different degrees of smoothness, a two-step method is proposed. In the case, one-step method for the smoother coefficient functions cannot be optimal. This drawback can be repaired by using the two-step(More)
In this paper, the varying-coefficient single-indexmodel (VCSIM) is proposed. It can be seen as a generalization of the semivaryingcoefficient model by changing its constant coefficient part to a nonparametric component, or a generalization of the partially linear single-indexmodel by replacing the constant coefficients of its linear part with varying(More)