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Copulas based inference for discrete or mixed data

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Authors : Rémillard, Bruno (Author of the conference)
CIRM (Publisher )

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Abstract : In this talk I will introduce the multilinear empirical copula for discrete or mixed data and its asymptotic behavior will be studied. This result will then be used to construct inference procedures for multivariate data. Applications for testing independence will be presented.

Keywords : dependence models; count data; copulas

MSC Codes :
62E20 - Asymptotic distribution theory in statistics
62G10 - Nonparametric hypothesis testing
62G20 - Nonparametric asymptotic efficiency
62H15 - Multivariate hypothesis testing

    Information on the Video

    Film maker : Hennenfent, Guillaume
    Language : English
    Available date : 10/03/16
    Conference Date : 23/02/2016
    Subseries : Research talks
    arXiv category : Statistics Theory
    Mathematical Area(s) : Probability & Statistics
    Format : MP4 (.mp4) - HD
    Video Time : 00:33:02
    Targeted Audience : Researchers
    Download : https://videos.cirm-math.fr/2016-02-23_Remillard.mp4

Information on the Event

Event Title : Thematic month on statistics - Week 4: Extremes, copulas and actuarial science / Mois thématique sur les statistiques - Semaine 4 : Extrêmes, copules et actuariat
Event Organizers : Boutahar, Mohamed ; Pommeret, Denys ; Royer-Carenzi, Manuela
Dates : 22/02/16 - 28/02/16
Event Year : 2016
Event URL : http://conferences.cirm-math.fr/1618.html

Citation Data

DOI : 10.24350/CIRM.V.18934103
Cite this video as: Rémillard, Bruno (2016). Copulas based inference for discrete or mixed data. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.18934103
URI : http://dx.doi.org/10.24350/CIRM.V.18934103

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