Abstract
Consider the semiparametric model Y ij = X i T β 0 + g ( t ij ) + e ij , where β 0 is a k × 1 vector of unknown parameters, g ( · ) is a function to be estimated and e ij are unobserved disturbances. A piecewise polynomial is proposed to approximate g and two least absolute deviation estimators of β 0 are obtained by using two weighting schemes: equal weight for each subject and equal weight for each measurement. Two local least absolute deviation estimators of g ( · ) are also obtained by replacing β 0 in this model with their least absolute deviation estimators and using a local linear approximation. The asymptotic distributions of the estimators of β 0 are derived. The asymptotic distributions of the local least absolute deviation estimators of g ( · ) at both interior and boundary points are also established. Finite sample properties of our procedures are studied through Monte Carlo simulations.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.