Aspects of Dependence in Generalized Farlie-Gumbel-Morgenstern Distributions

Amini, Mohammad; Nooghabi, Hadi Jabbari; Borzadaran, Gholam Reza Mohtashami

doi:10.1080/03610918.2011.568149

Cited by 13 publications

(6 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These results confirm the results of Amini et al (2010Amini et al ( , 2011. Finally, we explore the results using two actual example for PQD and NQD cases for more justifications.…”

Section: Discussionsupporting

confidence: 75%

“…Amini et al (2010Amini et al ( , 2011 compared the power of tests proposed by Kochar and Gupta (1987) in FGM distribution with those proposed by Güven and Kotz (2008) for testing independence against strict PQD or NQD. Some authors introduced a test statistic for testing independence against strict PQD or NQD; however, these tests have not been compared.…”

Section: Examplesmentioning

confidence: 99%

“…Some authors introduced a test statistic for testing independence against strict PQD or NQD; however, these tests have not been compared. So selecting the best test and improving the results obtained by Amini et al (2010Amini et al ( , 2011, we consider some rank tests and compare them with the class of tests proposed by Kochar and Gupta (1987) and the test statistic proposed by Güven and Kotz (2008) for testing independence against strict PQD or NQD in generalized FGM family.…”

Section: Examplesmentioning

confidence: 99%

“…The test maximizes the minimum power and possesses a monotone increasing power over the alternative hypothesis. Amini et al (2010Amini et al ( , 2011 used a dependence measure for the generalized FGM family in view of Kochar and Gupta (1987) and compared the power of tests proposed by them in absolutely continuous bivariate FGM distributions with those proposed by Güven and Kotz (2008).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Comparing the empirical powers of several independence tests in generalized FGM family

Zargar

Jabbari

Amini

2016

CSAM

Self Cite

View full text Add to dashboard Cite

The powers of some tests for independence hypothesis against positive (negative) quadrant dependence in generalized Farlie-Gumbel-Morgenstern distribution are compared graphically by simulation. Some of these tests are usual linear rank tests of independence. Two other possible rank tests of independence are locally most powerful rank test and a powerful nonparametric test based on the Cramér-von Mises statistic. We also evaluate the empirical power of the class of distribution-free tests proposed by Kochar and Gupta (1987) based on the asymptotic distribution of a U-statistic and the test statistic proposed by Güven and Kotz (2008) in generalized Farlie-Gumbel-Morgenstern distribution. Tests of independence are also compared for sample sizes n = 20, 30, 50, empirically. Finally, we apply two examples to illustrate the results.

show abstract

“…These results confirm the results of Amini et al (2010Amini et al ( , 2011. Finally, we explore the results using two actual example for PQD and NQD cases for more justifications.…”

Section: Discussionsupporting

confidence: 75%

Section: Examplesmentioning

confidence: 99%

Section: Examplesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Comparing the empirical powers of several independence tests in generalized FGM family

Zargar

Jabbari

Amini

2016

CSAM

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, a shortcoming of FGM copulas is that they do not allow modeling of high dependencies because their spearman's ρ is limited to [ −1 3 , 1 3 ]. To overcome this problem, many authors such as Huang and Kotz (1999), Bairamov and Kotz (2002), Girard (2002, 2009), Amini et al (2011) have tried to extend this family. Recently Klein and Christa (2011) proposed a class of copulas which contains F GM copulas as follows: A bivariate function C (u, v; θ, γ) = uv[1 + θϕ(u)…”

Section: B J P S -Accepted Manuscriptmentioning

confidence: 99%

A large class of new bivariate copulas and their properties

Sharifonnasabi¹,

Alamatsaz²,

Kazemi³

2018

Braz. J. Probab. Stat.

View full text Add to dashboard Cite

In this paper, we shall construct a large class of new bivariate copulas. This class happens to contain several known classes of copulas, such as Farlie-Gumbel-Morgenstern, Ali-Mikhail-Haq and Barnett-Gumbel, as its especial members. It is shown that the proposed copulas improve the range of values of correlation coefficient and thus they are more applicable in data modeling. We shall also reveal that the dependent properties of the base copula are preserved by the generated copula under certain conditions. Several members of the new class are introduced as instances and their range of correlation coefficients are computed.

show abstract

Analysis of Survival Data Under an Assumed Copula

Emura

Chen

2018

Analysis of Survival Data With Dependent Censoring

View full text Add to dashboard Cite

Aspects of Dependence in Generalized Farlie-Gumbel-Morgenstern Distributions

Cited by 13 publications

References 13 publications

Comparing the empirical powers of several independence tests in generalized FGM family

Comparing the empirical powers of several independence tests in generalized FGM family

A large class of new bivariate copulas and their properties

Analysis of Survival Data Under an Assumed Copula

Contact Info

Product

Resources

About