Estimation of a semiparametric transformation model

Linton, Oliver;Sperlich, Stefan;Van Keilegom, Ingrid
(2008) Annals of Statistics — Vol. 36, n° 2, p. 686-718 (2008)

Files

euclidaos.pdf
  • Open Access
  • Adobe PDF
  • 290.37 KB
Download

Details

Authors
Abstract
This paper proposes consistent estimators for transformation parameters in semiparametric models. The problem is to find the optimal transformation into the space of models with a predetermined regression structure like additive or multiplicative separability. We give results for the estimation of the transformation when the rest of the model is estimated non- or semi-parametrically and fulfills some consistency conditions. We propose two methods for the estimation of the transformation parameter maximizing a profile likelihood function or minimizing the mean squared distance from independence. First the problem of identification of such models is discussed. We then state asymptotic results for a general class of nonparametric estimators. Finally, we give some particular examples of nonparametric estimators of transformed separable models. The small sample performance is studied in several simulations.
Affiliations

Citations

  • APA
  • Chicago
  • FWB

Linton, O., Sperlich, S., & Van Keilegom, I. (2008). Estimation of a semiparametric transformation model. Annals of Statistics, 36(2), 686-718. https://doi.org/10.1214/009053607000000848 (Original work published 2008)