Testing tail monotonicity by constrained copula estimation

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<dc:creator>Gijbels, Irène</dc:creator>
<dc:date>2013-03-04</dc:date>
<dc:description xml:lang="es">Sumario: In this paper the interest is in testing for tail monotonicity dependence structures between two random variables. The main focus in the presentation of the statistical methodology is on left tail decreasingness, but the developed procedures can also be used for testing for other specific tail monotonicity dependence structures. In order to assess the p-values of the test statistic, we resample from a constrained copula estimator. This can be done in a nonparametric or in a parametric way. The main difficulty is the construction of a constrained estimator and the development of a resampling technique. The finite-sample performances of the proposed testing procedures are investigated in a simulation study and illustrations on real data examples are provided.</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/143600.do</dc:identifier>
<dc:language>spa</dc:language>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">Testing tail monotonicity by constrained copula estimation</dc:title>
<dc:relation xml:lang="es">En: Insurance : mathematics and economics. - Oxford : Elsevier, 1990- = ISSN 0167-6687. - 04/03/2013 Volumen 52 Número 2 - marzo 2013 </dc:relation>
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