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A new class of metric divergences on probability spaces and its applicability in statistics

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  • Ferdinand Österreicher
  • Igor Vajda

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  • Ferdinand Österreicher & Igor Vajda, 2003. "A new class of metric divergences on probability spaces and its applicability in statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(3), pages 639-653, September.
    • Handle: RePEc:spr:aistmt:v:55:y:2003:i:3:p:639-653
    DOI: 10.1007/BF02517812
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    References listed on IDEAS

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    1. Ayanendranath Basu & Bruce Lindsay, 1994. "Minimum disparity estimation for continuous models: Efficiency, distributions and robustness," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 46(4), pages 683-705, December.
    2. L. Györfi & I. Vajda & E. Meulen, 1996. "Minimum kolmogorov distance estimates of parameters and parametrized distributions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 43(1), pages 237-255, December.
    3. Pak, Ro Jin, 1996. "Minimum Hellinger distance estimation in simple linear regression models; distribution and efficiency," Statistics & Probability Letters, Elsevier, vol. 26(3), pages 263-269, February.
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    Citations

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    Cited by:

    1. Tsagris, Michail, 2014. "The k-NN algorithm for compositional data: a revised approach with and without zero values present," MPRA Paper 65866, University Library of Munich, Germany.
    2. Gómez-Lopera, J.F. & Martínez-Aroza, J. & Rodríguez-Valverde, M.A. & Cabrerizo-Vílchez, M.A. & Montes-Ruíz-Cabello, F.J., 2015. "Entropic image segmentation of sessile drops over patterned acetate," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 118(C), pages 239-247.
    3. Osán, Tristán M. & Bussandri, Diego G. & Lamberti, Pedro W., 2018. "Monoparametric family of metrics derived from classical Jensen–Shannon divergence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 336-344.
    4. Papastamoulis Panagiotis & Rattray Magnus, 2017. "Bayesian estimation of differential transcript usage from RNA-seq data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(5-6), pages 387-405, December.
    5. Tsagris, Michail, 2015. "A novel, divergence based, regression for compositional data," MPRA Paper 72769, University Library of Munich, Germany.
    6. Boussalis, Constantine & Dukalskis, Alexander & Gerschewski, Johannes, 2022. "Why It Matters What Autocrats Say: Assessing Competing Theories of Propaganda," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 70(3), pages 241-252.
    7. Yu, Xisheng, 2021. "A unified entropic pricing framework of option: Using Cressie-Read family of divergences," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    8. Yan Zhihua & Tang Xijin, 2020. "Exploring Evolution of Public Opinions on Tianya Club Using Dynamic Topic Models," Journal of Systems Science and Information, De Gruyter, vol. 8(4), pages 309-324, August.
    9. Tsagris, Michail & Preston, Simon & T.A. Wood, Andrew, 2016. "Improved classi cation for compositional data using the $\alpha$-transformation," MPRA Paper 67657, University Library of Munich, Germany.
    10. Michail Tsagris & Simon Preston & Andrew T. A. Wood, 2016. "Improved Classification for Compositional Data Using the α-transformation," Journal of Classification, Springer;The Classification Society, vol. 33(2), pages 243-261, July.
    11. Topsøe, Flemming, 2004. "Entropy and equilibrium via games of complexity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 340(1), pages 11-31.
    12. Osán, T.M. & Bussandri, D.G. & Lamberti, P.W., 2022. "Quantum metrics based upon classical Jensen–Shannon divergence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    13. Sagron, Ruth & Pugatch, Rami, 2021. "Universal distribution of batch completion times and time-cost tradeoff in a production line with arbitrary buffer size," European Journal of Operational Research, Elsevier, vol. 293(3), pages 980-989.
    14. Leila M Naeni & Hugh Craig & Regina Berretta & Pablo Moscato, 2016. "A Novel Clustering Methodology Based on Modularity Optimisation for Detecting Authorship Affinities in Shakespearean Era Plays," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-27, August.

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