An asymptotic test of independence for multivariate \(t\) and Cauchy random variables with applications
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Publication:1373381
DOI10.1016/0020-0255(96)00036-9zbMath0882.62050OpenAlexW2063885684MaRDI QIDQ1373381
Publication date: 17 December 1997
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0020-0255(96)00036-9
Hypothesis testing in multivariate analysis (62H15) Statistical aspects of information-theoretic topics (62B10) Asymptotic properties of parametric tests (62F05)
Related Items (8)
Mutual information as a measure of multivariate association: analytical properties and statistical estimation ⋮ Sampling distributions associated with the multivariate t distribution ⋮ On some entropy and divergence type measures of variability and dependence for mixed continuous and discrete variables ⋮ Dimensionless Measures of Variability and Dependence for Multivariate Continuous Distributions ⋮ Measuring stochastic dependence using \(\phi\)-divergence ⋮ Mathematical properties of the multivariate \(t\) distribution ⋮ On a measure of dependence based on fisher's information matrix ⋮ Measures of dependence for the multivariate t distribution with applications to the stock market
Cites Work
- A generalization of the Wishart distribution for the elliptical model and its moments for the multivariate t model
- A measure of total variability for the multivariate \(t\) distribution with applications to finance
- An informational measure of correlation
- Estimation of the parameters of a regression model with a multivariate t error variable
- Relative Entropy Measures of Multivariate Dependence
- A BIVARIATE GENERALIZATION OF STUDENT'S t-DISTRIBUTION, WITH TABLES FOR CERTAIN SPECIAL CASES
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