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Incremental Tree-Based Missing Data Imputation with Lexicographic Ordering

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  • Claudio Conversano

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  • Roberta Siciliano

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Abstract

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Suggested Citation

  • Claudio Conversano & Roberta Siciliano, 2009. "Incremental Tree-Based Missing Data Imputation with Lexicographic Ordering," Journal of Classification, Springer;The Classification Society, vol. 26(3), pages 361-379, December.
  • Handle: RePEc:spr:jclass:v:26:y:2009:i:3:p:361-379
    DOI: 10.1007/s00357-009-9038-8
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    File URL: http://hdl.handle.net/10.1007/s00357-009-9038-8
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    References listed on IDEAS

    as
    1. Iacus, Stefano M. & Porro, Giuseppe, 2007. "Missing data imputation, matching and other applications of random recursive partitioning," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 773-789, October.
    2. George Petrakos & Claudio Conversano & Gregory Farmakis & Francesco Mola & Roberta Siciliano & Photis Stavropoulos, 2004. "New ways of specifying data edits," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(2), pages 249-274, May.
    3. Jesús Barcena, María & Tusell, Fernando, 2004. "Fitting multivariate responses using scalar trees," Statistics & Probability Letters, Elsevier, vol. 69(3), pages 253-259, September.
    4. Siciliano, Roberta & Mola, Francesco, 2000. "Multivariate data analysis and modeling through classification and regression trees," Computational Statistics & Data Analysis, Elsevier, vol. 32(3-4), pages 285-301, January.
    5. J. G. Ibrahim & S. R. Lipsitz & M.‐H. Chen, 1999. "Missing covariates in generalized linear models when the missing data mechanism is non‐ignorable," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 173-190.
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    Citations

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    Cited by:

    1. Antonio D’Ambrosio & Massimo Aria & Roberta Siciliano, 2012. "Accurate Tree-based Missing Data Imputation and Data Fusion within the Statistical Learning Paradigm," Journal of Classification, Springer;The Classification Society, vol. 29(2), pages 227-258, July.
    2. Burim Ramosaj & Markus Pauly, 2019. "Predicting missing values: a comparative study on non-parametric approaches for imputation," Computational Statistics, Springer, vol. 34(4), pages 1741-1764, December.
    3. Lukasz Struski & Marek Śmieja & Jacek Tabor, 2020. "Pointed Subspace Approach to Incomplete Data," Journal of Classification, Springer;The Classification Society, vol. 37(1), pages 42-57, April.

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