The mixture approach for simulating bivariate distributions with specified correlations

被引:20
|
作者
Michael, JR
Schucany, WR
机构
[1] So Methodist Univ, Dept Stat Sci, Dallas, TX 75275 USA
[2] So Methodist Univ, Dept Stat Sci, Dallas, TX 75275 USA
来源
AMERICAN STATISTICIAN | 2002年 / 56卷 / 01期
关键词
Bayes; beta; conjugate prior; cool; exchangeable; gamma; generating; Gibbs sampling; hierarchical models; Markov chain Monte Carlo; posterior; uniform;
D O I
10.1198/000313002753631367
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The Mixture approach is an exact methodology for simulating families of bivariate distributions with specified correlation coefficients, some of which are new. It can accommodate the entire range of correlation coefficients, produces bivariate surfaces that are intuitively appealing, and is often remarkably easy to implement. The approach is introduced in a Bayesian context and demonstrated for the conjugate families of beta and gamma dis- tributions, with special attention given to the bivariate uniform. For these distributions, formulas for correlations have simple closed forms and computations are easy.
引用
收藏
页码:48 / 54
页数:7
相关论文
共 50 条
  • [1] Correlations in bivariate Pareto distributions
    Michael, Courtney Vanderford
    Dang, Xin
    JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2022, 92 (12) : 2501 - 2524
  • [2] Mixture of Bivariate Exponential Distributions
    Diawara, Norou
    Carpenter, Mark
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2010, 39 (15) : 2711 - 2720
  • [3] On bivariate and a mixture of bivariate Birnbaum-Saunders distributions
    Khosravi, Mohsen
    Kundu, Debasis
    Jamalizadeh, Ahad
    STATISTICAL METHODOLOGY, 2015, 23 : 1 - 17
  • [4] Simulating non-normal distributions with specified L-moments and L-correlations
    Headrick, Todd C.
    Pant, Mohan D.
    STATISTICA NEERLANDICA, 2012, 66 (04) : 422 - 441
  • [5] A family of multivariate binary distributions for simulating correlated binary variables with specified marginal means and correlations
    Qaqish, BF
    BIOMETRIKA, 2003, 90 (02) : 455 - 463
  • [6] BIVARIATE BETA MIXTURE MODEL WITH CORRELATIONS
    Trianasari, Nurvita
    Sumertajaya, I. Made
    Erfiani
    Mangku, I. Wayan
    COMMUNICATIONS IN MATHEMATICAL BIOLOGY AND NEUROSCIENCE, 2021,
  • [7] Bivariate Continuous Distributions with Specified Conditional Hazard Functions
    Balakrishnan, N.
    Castillo, Enrique
    Maria Sarabia, Jose
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2010, 39 (14) : 2473 - 2484
  • [8] CORRELATIONS AND CANONICAL-FORMS OF BIVARIATE DISTRIBUTIONS
    LANCASTER, HO
    ANNALS OF MATHEMATICAL STATISTICS, 1963, 34 (02): : 532 - &
  • [9] A new class of bivariate distributions and its mixture
    Sarhan, Ammar M.
    Balakrishnan, N.
    JOURNAL OF MULTIVARIATE ANALYSIS, 2007, 98 (07) : 1508 - 1527
  • [10] A Mixture Model of Two Bivariate Weibull Distributions
    Turkan, Ayca Hatice
    Calis, Nazif
    GAZI UNIVERSITY JOURNAL OF SCIENCE, 2018, 31 (02): : 643 - 658