Fitting generalized linear models with unspecified link function: A P-spline approach
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References listed on IDEAS
- Yu Y. & Ruppert D., 2002. "Penalized Spline Estimation for Partially Linear Single-Index Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1042-1054, December.
- Marx, Brian D. & Eilers, Paul H. C., 1998. "Direct generalized additive modeling with penalized likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 28(2), pages 193-209, August.
- Horowitz, Joel L, 2001. "Nonparametric Estimation of a Generalized Additive Model with an Unknown Link Function," Econometrica, Econometric Society, vol. 69(2), pages 499-513, March.
- Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521785167, June.
- Kaiser, Mark S., 1997. "Maximum likelihood estimation of link function parameters," Computational Statistics & Data Analysis, Elsevier, vol. 24(1), pages 79-87, March.
- Roger Klein & Richard Spady & Andrew Weiss, 1991. "Factors Affecting the Output and Quit Propensities of Production Workers," Review of Economic Studies, Oxford University Press, vol. 58(5), pages 929-953.
- Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521780506, June.
- Scallan, A. & Gilchrist, R. & Green, M., 1984. "Fitting parametric link functions in generalised linear models," Computational Statistics & Data Analysis, Elsevier, vol. 2(1), pages 37-49, June.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Ferrara, Giancarlo & Vidoli, Francesco, 2017. "Semiparametric stochastic frontier models: A generalized additive model approach," European Journal of Operational Research, Elsevier, vol. 258(2), pages 761-777.
- Stoklosa, Jakub & Huggins, Richard M., 2012. "A robust P-spline approach to closed population capture–recapture models with time dependence and heterogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 408-417.
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