Journal article
A note on estimating a partly linear model under monotonicity constraints
Journal of statistical planning and inference, Vol.107(1), pp.343-351
2002
DOI: 10.1016/S0378-3758(02)00262-8
Abstract
We consider asymptotic properties of the least-squares estimator of a partly linear regression model when the nonparametric component is subject to monotonicity constraints. We show that the least-squares estimator of the finite-dimensional regression coefficient is root-n consistent and asymptotically normal. We also show that the isotonic estimator of the monotone nonparametric function at a fixed point is cube root-n consistent, and apart from a scale constant, has the same limiting distribution in nonparametric monotone density estimation and isotonic regression derived by Prakasa Rao (Sankhya Ser. A 31 (1969) 23) and Brunk (In: M.L. Puri (Ed.), Nonparametric Techniques in Statistical Inference, Cambridge University Press, Cambridge, 1970).
Details
- Title: Subtitle
- A note on estimating a partly linear model under monotonicity constraints
- Creators
- Jian Huang - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Journal of statistical planning and inference, Vol.107(1), pp.343-351
- Publisher
- Elsevier B.V
- DOI
- 10.1016/S0378-3758(02)00262-8
- ISSN
- 0378-3758
- eISSN
- 1873-1171
- Language
- English
- Date published
- 2002
- Academic Unit
- Statistics and Actuarial Science
- Record Identifier
- 9984257737802771
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