Generalized information matrix tests for copulas
نویسندگان
چکیده
منابع مشابه
Generalized Information Matrix Tests for Detecting Model Misspecification
Generalized Information Matrix Tests (GIMTs) have recently been used for detecting the presence of misspecification in regression models in both randomized controlled trials and observational studies. In this paper, a unified GIMT framework is developed for the purpose of identifying, classifying, and deriving novel model misspecification tests for finite-dimensional smooth probability models. ...
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Often of primary interest in the analysis of multivariate data are the copula parameters describing the dependence among the variables, rather than the univariate marginal distributions. Since the ranks of a multivariate dataset are invariant to changes in the univariate marginal distributions, rank-based estimators are natural candidates for semiparametric copula estimation. Asymptotic informa...
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In 2004, Rodr'{i}guez-Lallena and '{U}beda-Flores have introduced a class of bivariate copulas which generalizes some known families such as the Farlie-Gumbel-Morgenstern distributions. In 2006, Dolati and '{U}beda-Flores presented multivariate generalizations of this class. Then in 2011, Kim et al. generalized Rodr'{i}guez-Lallena and '{U}beda-Flores' study to any given copula family. But ther...
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Durante et al. (2007) introduced a class of bivariate copulas depending on two generators which generalizes some known families such as the Archimedean copulas. In this paper we provide some result on properties of this family when the generators are certain univariate survival functions.
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A goodness-of-fit test for exchangeable Archimedean copulas is presented. In a large-scale simulation study it is shown that the test performs well according to the error probability of the first kind and the power under several alternatives, especially in large dimensions. The proposed test is compared to other known tests for Archimedean copulas. In contrast to the latter, the former is simpl...
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ژورنال
عنوان ژورنال: Econometric Reviews
سال: 2019
ISSN: 0747-4938,1532-4168
DOI: 10.1080/07474938.2018.1514023