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Comments on: Model-free model-fitting and predictive distributions

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  • Stefan Sperlich

Abstract

Discussing the paper “Model-free model-fitting and predictive distributions” by Politis ( 2013 ), we propose to extend this procedure to semiparametric and parametric mixed effects models (MEM) as in practice, these are probably the most popular ones for prediction. Specifically, combining Politis’ prediction method with procedures from Lombardía and Sperlich (Comput. Stat. Data Anal. 56:2903–2917, 2012 ) and González-Manteiga et al. (J. Multivar. Anal. 114:288–302, 2013 ) yields new MEM-based MF/MB point and interval predictors which can be used for example for small area statistics. Combining Politis’ idea with nonparametric matching estimators may also yield improved (point and interval) estimators for treatment effects and policy evaluation. Copyright Sociedad de Estadística e Investigación Operativa 2013

Suggested Citation

  • Stefan Sperlich, 2013. "Comments on: Model-free model-fitting and predictive distributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 227-233, June.
  • Handle: RePEc:spr:testjl:v:22:y:2013:i:2:p:227-233
    DOI: 10.1007/s11749-013-0318-6
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    References listed on IDEAS

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    1. Stefan Sperlich & María José Lombardía, 2010. "Local polynomial inference for small area statistics: estimation, validation and prediction," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(5), pages 633-648.
    2. Nielsen, Jens Perch & Sperlich, Stefan, 2003. "Prediction of Stock Returns: A New Way to Look at It," ASTIN Bulletin, Cambridge University Press, vol. 33(2), pages 399-417, November.
    3. Dimitris Politis, 2013. "Rejoinder on: Model-free model-fitting and predictive distributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 240-250, June.
    4. J. D. Opsomer & G. Claeskens & M. G. Ranalli & G. Kauermann & F. J. Breidt, 2008. "Non‐parametric small area estimation using penalized spline regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(1), pages 265-286, February.
    5. Claeskens,Gerda & Hjort,Nils Lid, 2008. "Model Selection and Model Averaging," Cambridge Books, Cambridge University Press, number 9780521852258.
    6. M. P. Wand, 2003. "Smoothing and mixed models," Computational Statistics, Springer, vol. 18(2), pages 223-249, July.
    7. Alberto Abadie & Guido W. Imbens, 2008. "On the Failure of the Bootstrap for Matching Estimators," Econometrica, Econometric Society, vol. 76(6), pages 1537-1557, November.
    8. Chris Elbers & Jean O. Lanjouw & Peter Lanjouw, 2003. "Micro--Level Estimation of Poverty and Inequality," Econometrica, Econometric Society, vol. 71(1), pages 355-364, January.
    9. José Lombardía, María & Sperlich, Stefan, 2012. "A new class of semi-mixed effects models and its application in small area estimation," Computational Statistics & Data Analysis, Elsevier, vol. 56(10), pages 2903-2917.
    10. María José Lombardía & Stefan Sperlich, 2008. "Semiparametric inference in generalized mixed effects models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(5), pages 913-930, November.
    11. Jiming Jiang & P. Lahiri, 2006. "Mixed model prediction and small area estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 15(1), pages 1-96, June.
    12. Dimitris Politis, 2013. "Model-free model-fitting and predictive distributions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 183-221, June.
    13. González Manteiga, Wenceslao & Lombardía, María José & Martínez Miranda, María Dolores & Sperlich, Stefan, 2013. "Kernel smoothers and bootstrapping for semiparametric mixed effects models," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 288-302.
    14. Salvati, Nicola & Chandra, Hukum & Giovanna Ranalli, M. & Chambers, Ray, 2010. "Small area estimation using a nonparametric model-based direct estimator," Computational Statistics & Data Analysis, Elsevier, vol. 54(9), pages 2159-2171, September.
    15. Alberto Abadie & Guido W. Imbens, 2006. "Large Sample Properties of Matching Estimators for Average Treatment Effects," Econometrica, Econometric Society, vol. 74(1), pages 235-267, January.
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