Presentation 2019-07-26
A study on asymptotically unbiased estimators of an FGM copula
Shuhei Ota, Mitsuhiro Kimura,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) A copula, one of the multivariate distributions, is known as a useful tool for dependence modeling because they can express high and non-linear correlations of random variables. Thus, parameter estimation for copulas is effective in analyzing dependence structures among data. However, it is computationally hard work because copulas have many parameters such as marginal parameters and dependence parameters in general. For example, a $d$-variate Farlie-Gumbel-Morgenstern (FGM) copula has $2^d-d-1$ dependence parameters, and therefore the ordinary maximum likelihood estimation (MLE) is not practical from the viewpoint of the computational complexity. In this study, we present a computable estimation method for the FGM copula by using the theory of inference functions for margins. Moreover, we prove that the estimator holds asymptotic unbiasedness.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Inference functions for margins / Maximum likelihood estimation / FGM copula / Asymptotic unbiasedness
Paper # R2019-15
Date of Issue 2019-07-19 (R)

Conference Information
Committee R
Conference Date 2019/7/26(1days)
Place (in Japanese) (See Japanese page)
Place (in English) Ichinoseki Cultural Center
Topics (in Japanese) (See Japanese page)
Topics (in English) Reliability Theory, Communication Network Reliability, Reliability General
Chair Akira Asato(Fujitsu)
Vice Chair Tadashi Dohi(Hiroshima Univ.)
Secretary Tadashi Dohi(Hosei Univ.)
Assistant Hiroyuki Okamura(Hiroshima Univ.) / Shinji Yokogawa(Univ. of Electro-Comm.)

Paper Information
Registration To Technical Committee on Reliability
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A study on asymptotically unbiased estimators of an FGM copula
Sub Title (in English)
Keyword(1) Inference functions for margins
Keyword(2) Maximum likelihood estimation
Keyword(3) FGM copula
Keyword(4) Asymptotic unbiasedness
1st Author's Name Shuhei Ota
1st Author's Affiliation Kanagawa University(Kanagawa Univ.)
2nd Author's Name Mitsuhiro Kimura
2nd Author's Affiliation Hosei University(Hosei Univ.)
Date 2019-07-26
Paper # R2019-15
Volume (vol) vol.119
Number (no) R-150
Page pp.pp.7-12(R),
#Pages 6
Date of Issue 2019-07-19 (R)