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Local Polynomial Kernel Regression for Generalized Linear Models and Quasi-Likelihood Functions
Abstract
We investigate the extension of the nonparametric regression technique of local polynomial fitting with a kernel weight to generalized linear models and quasi-likelihood contexts. In the ordinary regression case, local polynomial fitting has been seen to have several appealing features in terms of intuitive and mathematical simplicity. One noteworthy feature is the better performance near the boundaries compared to the traditional kernel regression estimators. These properties are shown to carry over to generalized linear model and quasi-likelihood settings. We also derive the asymptotic distributions of the proposed class of estimators that allow for straightforward interpretation and extensions of state-of-the-art bandwidth selection methods.
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(2005) · Statistics for Biology and Health · doi:10.1007/0-387-27255-0_9 · Cited by 20,133
McCullagh, P., & Nelder, J. A. (1989) · doi:10.1007/978-1-4899-3242-6 · Cited by 16,836
Brown, R. A., Hastie, T. J., & Tibshirani, R. J. (1991) · Biometrics · doi:10.2307/2532174 · Cited by 8,176
Koyak, R. A., Hastie, T. J., & Tibshirani, R. J. (1991) · Journal of the American Statistical Association · doi:10.2307/2290538 · Cited by 7,596
Nelder, J. A., & Wedderburn, R. W. M. (1972) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2344614 · Cited by 7,194
Spline Models for Observational Data.
Muller, H.-G., & Wahba, G. (1991) · Journal of the American Statistical Association · doi:10.2307/2290434 · Cited by 4,928
Generalized Linear Models (2nd ed.).
Therneau, T. M., McCullagh, P., & Nelder, J. A. (1993) · Journal of the American Statistical Association · doi:10.2307/2290358 · Cited by 4,907
Spline Models for Observational Data
Wahba, G. (1990) · doi:10.1137/1.9781611970128 · Cited by 4,184
Nadaraya, E. A. (1964) · Theory of Probability & Its Applications · doi:10.1137/1109020 · Cited by 3,462
Watson, G. S. (1964) · PUB – Publications at Bielefeld University (Bielefeld University) · Cited by 2,661
Cited by
Hainmueller, J., Mummolo, J., & Xu, Y. (2019) · Political Analysis · doi:10.1017/pan.2018.46 · Cited by 959
The econometrics of financial markets
Pagan, A. (1996) · Journal of Empirical Finance · doi:10.1016/0927-5398(95)00020-8 · Cited by 873
Chapter 38 Applied nonparametric methods
Härdle, W., & Linton, O. (1994) · Handbook of Econometrics · doi:10.1016/s1573-4412(05)80007-8 · Cited by 325
Metadata
- Authors
- Fan, J., Heckman, N. E., & Wand, M. P.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1995-03
- Volume
- 90
- Issue
- 429
- Pages
- 141-150
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2064385888
- Cited by
- 375
- References
- 38
- FWCI
- 12.15
- Type
- journal article
- Language
- en
- Open access
- closed
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- Fan, J., Heckman, N. E., & Wand, M. P. (1995). Local Polynomial Kernel Regression for Generalized Linear Models and Quasi-Likelihood Functions. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1995.10476496
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