Estimation of the Error Density in a Semiparametric Transformation Model
(2011) , 26 pages
Files
ISBADP2011-23_Estimationoftheerrordensityin.pdf
Open Access - Adobe PDF
- 411.66 KB
Details
- Authors
- Abstract
- Consider the semiparametric transformation model Λθο(Y) = m(X)+ε, where θο is an unknown finite dimensional parameter, the functions Λ θ ο and m are smooth, ε is independent of X, and (ε) = 0 We propose a kernel-type estimator of the density of the error ε, and prove its asymptotic normality. The estimated errors, which lie at the basis of this estimator, are obtained from a profile likelihood estimator of θο and a nonparametric kernel estimator of m. The practical performance of the proposed density estimator is evaluated in a simulation study.
- Affiliations
Citations
Samb, R., Heuchenne, C., & Van Keilegom, I. (2011). Estimation of the Error Density in a Semiparametric Transformation Model (ISBA Discussion Paper 2011/23). https://hdl.handle.net/2078.5/210528