an:07178853
Zbl 07178853
Kloodt, Nick; Neumeyer, Natalie
Specification tests in semiparametric transformation models --- a multiplier bootstrap approach
EN
Comput. Stat. Data Anal. 145, Article ID 106908, 24 p. (2020).
00447811
2020
j
62
box-Cox transformation; lack-of-fit test; multiplier bootstrap; nonparametric regression; significance of covariates; U-statistics; Yeo-Johnson transformation
Summary: Semiparametric transformation models are considered, where after pre-estimation of a parametric transformation of the response the data are modeled by means of nonparametric regression. Subsequent procedures for testing lack-of-fit of the regression function and for significance of covariates are suggested. In contrast to existing procedures, the tests are asymptotically not influenced by the pre-estimation of the transformation in the sense that they have the same asymptotic distribution as in regression models without transformation. Validity of a multiplier bootstrap procedure is shown which is easier to implement and much less computationally demanding than bootstrap procedures based on the transformation model. In a simulation study the superior performance of the procedure in comparison with its existing competitors is demonstrated.
Reviewer (Berlin)