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Fitting generalized linear models with unspecified link function: A P-spline approach

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  • Muggeo, Vito M.R.
  • Ferrara, Giancarlo

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  • Muggeo, Vito M.R. & Ferrara, Giancarlo, 2008. "Fitting generalized linear models with unspecified link function: A P-spline approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2529-2537, January.
  • Handle: RePEc:eee:csdana:v:52:y:2008:i:5:p:2529-2537
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    1. 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.
    2. 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.
    3. 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.
    4. Kaiser, Mark S., 1997. "Maximum likelihood estimation of link function parameters," Computational Statistics & Data Analysis, Elsevier, vol. 24(1), pages 79-87, March.
    5. Roger Klein & Richard Spady & Andrew Weiss, 1991. "Factors Affecting the Output and Quit Propensities of Production Workers," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(5), pages 929-953.
    6. Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521780506.
    7. 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.
    8. Daryl Pregibon, 1980. "Goodness of Link Tests for Generalized Linear Models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(1), pages 15-24, March.
    9. Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521785167.
    10. Jianhua Z. Huang & Linxu Liu, 2006. "Polynomial Spline Estimation and Inference of Proportional Hazards Regression Models with Flexible Relative Risk Form," Biometrics, The International Biometric Society, vol. 62(3), pages 793-802, September.
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    Cited by:

    1. Federico Belotti & Giancarlo Ferrara, 2019. "Imposing monotonicity in stochastic frontier models: an iterative nonlinear least squares procedure," CEIS Research Paper 462, Tor Vergata University, CEIS, revised 29 Jan 2021.
    2. 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.
    3. 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.
    4. ferrara, giancarlo & campagna, arianna & bucci, valeria & atella, vincenzo, 2021. "Presumptive taxation and firms’ efficiency: an integrated approach for tax compliance analysis," MPRA Paper 111516, University Library of Munich, Germany.
    5. Guilherme Pumi & Cristine Rauber & Fábio M. Bayer, 2020. "Kumaraswamy regression model with Aranda-Ordaz link function," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(4), pages 1051-1071, December.
    6. Giancarlo Ferrara & Arianna Campagna & Vincenzo Atella, 2019. "Disentangling tax evasion from inefficiency in firms tax declaration: an integrated approach," CEIS Research Paper 468, Tor Vergata University, CEIS, revised 06 Sep 2019.

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