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Volumn , Issue , 2010, Pages 581-588

Ordinary least squares for histogram data based on Wasserstein distance

Author keywords

Histogram data; Ordinary least squares; Probability distribution function; Wasserstein distance

Indexed keywords

DISTRIBUTION FUNCTIONS; PROBABILITY DISTRIBUTIONS; REGRESSION ANALYSIS;

EID: 84869183326     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-7908-2604-3_60     Document Type: Conference Paper
Times cited : (20)

References (10)
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  • 2
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    • (2000) Studies in Classification, Data Analysis and Knowledge Organisation
    • Bock, H.H.1    Diday, E.2
  • 5
    • 0001529786 scopus 로고
    • Asymptotic minimax character of the sample distribution function and of the classical multinomial estimator
    • DVORETZKY, A., KIEFER, J. and WOLFOWITZ, J. (1956): Asymptotic minimax character of the sample distribution function and of the classical multinomial estimator. Annals of Mathematical Statistics 27 (3), 642-669.
    • (1956) Annals of Mathematical Statistics , vol.27 , Issue.3 , pp. 642-669
    • Dvoretzky, A.1    Kiefer, J.2    Wolfowitz, J.3
  • 6
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    • On choosing and bounding probability metrics
    • GIBBS, A.L. and SU, F.E. (2002): On choosing and bounding probability metrics. Intl. Stat. Rev. 7 (3), 419-435.
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    • Gibbs, A.L.1    Su, F.E.2
  • 7
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    • Dynamic clustering of histograms using wasserstein metric
    • Rizzi, A. Vichi, M. (eds.), Physica-Verlag, Berlin
    • IRPINO, A., LECHEVALLIER, Y. and VERDE, R. (2006): Dynamic clustering of histograms using Wasserstein metric. In: Rizzi, A., Vichi, M. (eds.) COMPSTAT 2006. Physica-Verlag, Berlin, 869-876.
    • (2006) COMPSTAT 2006 , pp. 869-876
    • Irpino, A.1    Lechevallier, Y.2    Verde, R.3
  • 8
    • 58949098840 scopus 로고    scopus 로고
    • A new wasserstein based distance for the hierarchical clustering of histogram symbolic data
    • Batanjeli, V. Bock, H.H. Ferligoj, A. Ziberna, A. (eds.), Springer, Berlin
    • IRPINO, A. and VERDE, R. (2006): A new Wasserstein based distance for the hierarchical clustering of histogram symbolic data. In: Batanjeli, V., Bock, H.H., Ferligoj, A., Ziberna, A. (eds.) Data Science and Classification, IFCS 2006. Springer, Berlin, 185-192.
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  • 9
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    • Comparing histogram data using a mahalanobis-wasserstein distance
    • Brito, P. (eds.), Physica-Verlag, Springer, Berlin
    • VERDE, R. and IRPINO, A.(2008): Comparing Histogram data using a Mahalanobis-Wasserstein distance. In: Brito, P. (eds.) COMPSTAT 2008. Physica-Verlag, Springer, Berlin, 77-89.
    • (2008) COMPSTAT 2008 , pp. 77-89
    • Verde, R.1    Irpino, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.