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Binary trees for dissimilarity data

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  • Piccarreta, Raffaella
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    Abstract

    Binary segmentation procedures (in particular, classification and regression trees) are extended to study the relation between dissimilarity data and a set of explanatory variables. The proposed split criterion is very flexible, and can be applied to a wide range of data (e.g., mixed types of multiple responses, longitudinal data, sequence data). Also, it can be shown to be an extension of well-established criteria introduced in the literature on binary trees.

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    File URL: http://www.sciencedirect.com/science/article/B6V8V-4Y5BM8B-1/2/ba3eaa1712dd2341a2c790e568e6c46d
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    Bibliographic Info

    Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

    Volume (Year): 54 (2010)
    Issue (Month): 6 (June)
    Pages: 1516-1524

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    Handle: RePEc:eee:csdana:v:54:y:2010:i:6:p:1516-1524

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    Web page: http://www.elsevier.com/locate/csda

    Related research

    Keywords: Dissimilarity matrix Classification and regression trees Binary segmentation Multivariate responses Perception data Ecological data;

    References

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    1. Briand, Bénédicte & Ducharme, Gilles R. & Parache, Vanessa & Mercat-Rommens, Catherine, 2009. "A similarity measure to assess the stability of classification trees," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1208-1217, February.
    2. 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.
    3. Raffaella Piccarreta & Francesco C. Billari, 2007. "Clustering work and family trajectories by using a divisive algorithm," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(4), pages 1061-1078.
    4. Cees H. Elzinga, 2005. "Combinatorial Representations of Token Sequences," Journal of Classification, Springer, vol. 22(1), pages 87-118, June.
    5. Kim, Ji-Hyun, 2009. "Estimating classification error rate: Repeated cross-validation, repeated hold-out and bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 53(11), pages 3735-3745, September.
    6. Henk Kiers & Donatella Vicari & Maurizio Vichi, 2005. "Simultaneous classification and multidimensional scaling with external information," Psychometrika, Springer, vol. 70(3), pages 433-460, September.
    7. Dine, Abdessamad & Larocque, Denis & Bellavance, François, 2009. "Multivariate trees for mixed outcomes," Computational Statistics & Data Analysis, Elsevier, vol. 53(11), pages 3795-3804, September.
    8. Sexton, Joseph & Laake, Petter, 2009. "Standard errors for bagged and random forest estimators," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 801-811, January.
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    Citations

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    Cited by:
    1. Marco Bonetti & Raffaella Piccarreta & Gaia Salford, 2013. "Parametric and Nonparametric Analysis of Life Courses: An Application to Family Formation Patterns," Demography, Springer, vol. 50(3), pages 881-902, June.

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