Estimation of a common mean vector in bivariate meta-analysis under the FGM copula
Statistics, 2019We propose a bivariate Farlie–Gumbel–Morgenstern (FGM) copula model for bivariate meta-analysis, and develop a maximum likelihood estimator for the common mean vector.
Yoshihiko Konno, Takeshi Emura
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Bivariate dependence measures and bivariate competing risks models under the generalized FGM copula
Statistical Papers, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Takeshi Emura, Emura Takeshi
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Risk Concentration Based on the Tail Distortion Risk Measure under Generalized FGM Copula
2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI), 2016Risk concentration is used as a measurement of diversification benefits in the context of risk concentration. The tail distortion risk measure, which was introduced in Zhu and Li (2012), has attracted increasing interest recently. In this paper, We investigate the second-order asymptotics of the risk concentration based on the tail distortion risk ...
Guangjun Shen
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Constructing symmetric generalized FGM copulas by means of certain univariate distributions [PDF]
, 2004 In this paper we focus on symmetric generalized Fairlie-Gumbel-Morgenstern (or symmetric Sarmanov) copulas which are characterized by means of so-called generator functions. In particular, we introduce a class of generator functions which is based on univariate distributions with certain properties.
Fischer, Matthias J., Klein, Ingo
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Copula-based direct utility models for correlated choice alternatives [PDF]
Quantitative Marketing and Economics, 2022 We propose a general framework of copula-based direct utility models and suggest two approaches (Gaussian and FGM approaches) that can accommodate correlations among unobserved utilities. We investigate how and in which directions the biases in parameter
Chul Kim, Duk Bin Jun, Sungho Park
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Copula-Based Estimation Methods for a Common Mean Vector for Bivariate Meta-Analyses [PDF]
Symmetry, 2022 Traditional bivariate meta-analyses adopt the bivariate normal model. As the bivariate normal distribution produces symmetric dependence, it is not flexible enough to describe the true dependence structure of real meta-analyses.
Yoshihiko Konno +2 more
exaly +2 more sources
FGM generated Archimedean copulas with concave multiplicative generators
2021Summary: The Farlie-Gumble-Morgenstren (FGM) family and archimedean family are the most popular parametric families of copulas. In the present paper, we propose an extension of archimedean copulas with concave multiplicative generators in the style of FGM family.
Doodman, N. +3 more
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Stochastic representation of FGM copulas using multivariate Bernoulli random variables
Computational Statistics & Data Analysis, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Christopher Blier-Wong +2 more
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A new extension of the FGM copula with an application in reliability
Communications in Statistics - Theory and Methods, 2020We propose a new symmetric extension of the bivariate Farlie-Gumbel-Morgenstern (FGM) copula with given marginals.
Rasha Ebaid +3 more
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Constructing Generalized FGM Copulas by Means of Certain Univariate Distributions
Metrika, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fischer, Matthias, Klein, Ingo
openaire +2 more sources