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Combining non-parametric models with logistic regression: an application to motor vehicle injury data

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  • Kuhnert, Petra M.
  • Do, Kim-Anh
  • McClure, Rod

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  • Kuhnert, Petra M. & Do, Kim-Anh & McClure, Rod, 2000. "Combining non-parametric models with logistic regression: an application to motor vehicle injury data," Computational Statistics & Data Analysis, Elsevier, vol. 34(3), pages 371-386, September.
    • Handle: RePEc:eee:csdana:v:34:y:2000:i:3:p:371-386
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    References listed on IDEAS

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    1. Greenland, S., 1989. "Modeling and variable selection in epidemiologic analysis," American Journal of Public Health, American Public Health Association, vol. 79(3), pages 340-349.
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    1. Barrios, Erniel B. & Mina, Christian D., 2009. "Profiling Poverty with Multivariate Adaptive Regression Splines," Discussion Papers DP 2009-29, Philippine Institute for Development Studies.
    2. Petra M. Kuhnert & Kerrie Mengersen & Peter Tesar, 2003. "Bridging the Gap between Different Statistical Approaches: An Integrated Framework for Modelling," International Statistical Review, International Statistical Institute, vol. 71(2), pages 335-368, August.
    3. Radwan, Amr & Gil, José M., 2014. "On the Nexus between Economic and Obesity Crisis in Spain: Parametric and Nonparametric Analysis of the Role of Economic Factors on Obesity Prevalence," 88th Annual Conference, April 9-11, 2014, AgroParisTech, Paris, France 170341, Agricultural Economics Society.
    4. Muhammad Muhitur Rahman & Md Kamrul Islam & Ammar Al-Shayeb & Md Arifuzzaman, 2022. "Towards Sustainable Road Safety in Saudi Arabia: Exploring Traffic Accident Causes Associated with Driving Behavior Using a Bayesian Belief Network," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    5. David Feldman & Shulamith Gross, 2005. "Mortgage Default: Classification Trees Analysis," The Journal of Real Estate Finance and Economics, Springer, vol. 30(4), pages 369-396, June.
    6. Barrios, Erniel B. & Mina, Christian D., 2009. "Profiling Poverty with Multivariate Adaptive Regression Splines," Discussion Papers DP 2009-29, Philippine Institute for Development Studies.
    7. Lkhagvadorj Munkhdalai & Tsendsuren Munkhdalai & Oyun-Erdene Namsrai & Jong Yun Lee & Keun Ho Ryu, 2019. "An Empirical Comparison of Machine-Learning Methods on Bank Client Credit Assessments," Sustainability, MDPI, vol. 11(3), pages 1-23, January.
    8. Chang, Li-Yen, 2014. "Analysis of bilateral air passenger flows: A non-parametric multivariate adaptive regression spline approach," Journal of Air Transport Management, Elsevier, vol. 34(C), pages 123-130.
    9. Hu, Xiaolu & Huang, Haozhi & Pan, Zheyao & Shi, Jing, 2019. "Information asymmetry and credit rating: A quasi-natural experiment from China," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 132-152.
    10. Fu, Chong Yau, 2004. "Combining loglinear model with classification and regression tree (CART): an application to birth data," Computational Statistics & Data Analysis, Elsevier, vol. 45(4), pages 865-874, May.
    11. Lee, Tian-Shyug & Chiu, Chih-Chou & Chou, Yu-Chao & Lu, Chi-Jie, 2006. "Mining the customer credit using classification and regression tree and multivariate adaptive regression splines," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 1113-1130, February.

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