Classification with incomplete functional covariates
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DOI: 10.1016/j.spl.2018.03.010
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References listed on IDEAS
- Bugni, Federico A., 2012.
"Specification Test For Missing Functional Data,"
Econometric Theory, Cambridge University Press, vol. 28(5), pages 959-1002, October.
- Federico A Bugni, 2010. "Specification Test for Missing Functional Data," Working Papers 10-41, Duke University, Department of Economics.
- Majid Mojirsheibani & Timothy Reese, 2017. "Kernel regression estimation for incomplete data with applications," Statistical Papers, Springer, vol. 58(1), pages 185-209, March.
- Bravo, Francesco, 2015. "Semiparametric estimation with missing covariates," Journal of Multivariate Analysis, Elsevier, vol. 139(C), pages 329-346.
- Aurore Delaigle & Peter Hall, 2013. "Classification Using Censored Functional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(504), pages 1269-1283, December.
- repec:pri:cheawb:case_paxson_economic_status_paper is not listed on IDEAS
- Anne Case & Darren Lubotsky & Christina Paxson, 2002.
"Economic Status and Health in Childhood: The Origins of the Gradient,"
American Economic Review, American Economic Association, vol. 92(5), pages 1308-1334, December.
- Anne Case & Darren Lubotsky & Christina Paxson, 2001. "Economic Status and Health in Childhood: The Origins of the Gradient," NBER Working Papers 8344, National Bureau of Economic Research, Inc.
- Anne Case & Darren Lubotsky & Christina Paxson, 2002. "Economic status and health in childhood: the origins of the gradient," Working Papers 262, Princeton University, Woodrow Wilson School of Public and International Affairs, Center for Health and Wellbeing..
- Timothy Reese & Majid Mojirsheibani, 2017. "On the $$L_p$$ L p norms of kernel regression estimators for incomplete data with applications to classification," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(1), pages 81-112, March.
- Antonio Cuevas & Manuel Febrero & Ricardo Fraiman, 2007. "Robust estimation and classification for functional data via projection-based depth notions," Computational Statistics, Springer, vol. 22(3), pages 481-496, September.
- C. Abraham & G. Biau & B. Cadre, 2006. "On the Kernel Rule for Function Classification," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 58(3), pages 619-633, September.
- Chung Chang & Yakuan Chen & R. Ogden, 2014. "Functional data classification: a wavelet approach," Computational Statistics, Springer, vol. 29(6), pages 1497-1513, December.
- Ferraty, F. & Vieu, P., 2003. "Curves discrimination: a nonparametric functional approach," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 161-173, October.
- repec:pri:cheawb:case_paxson_economic_status_paper.pdf is not listed on IDEAS
- A. Delaigle & P. Hall & N. Bathia, 2012. "Componentwise classification and clustering of functional data," Biometrika, Biometrika Trust, vol. 99(2), pages 299-313.
- David Kraus, 2015. "Components and completion of partially observed functional data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 77(4), pages 777-801, September.
- Majid Mojirsheibani & Zahra Montazeri, 2007. "Statistical classification with missing covariates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(5), pages 839-857, November.
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Cited by:
- Kraus, David, 2019. "Inferential procedures for partially observed functional data," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 583-603.
- Kraus, David & Stefanucci, Marco, 2020. "Ridge reconstruction of partially observed functional data is asymptotically optimal," Statistics & Probability Letters, Elsevier, vol. 165(C).
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Keywords
Classification; Pattern recognition; Functional covariates; Supervised learning;All these keywords.
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