On some entropy and divergence type measures of variability and dependence for mixed continuous and discrete variables

DOI10.1016/j.jspi.2008.02.011zbMath1146.62002OpenAlexW1969903848MaRDI QIDQ951048

B. E. Eshmatov

Publication date: 29 October 2008

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2008.02.011

zbMATH Keywords

variabilitymutual informationlocation modelmultivariate \(t\) distributionmixed variableselliptic distributionPearson type II and VII distributions

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Measures of association (correlation, canonical correlation, etc.) (62H20) Statistical aspects of information-theoretic topics (62B10)

Related Items (5)

Unnamed Item ⋮ Analyzing supersaturated designs with entropic measures ⋮ Residual and past entropy in actuarial science and survival models ⋮ On some entropy and divergence type measures of variability and dependence for mixed continuous and discrete variables ⋮ Rényi entropy rate for Gaussian processes

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A Mathematical Theory of Communication
• A measure for total variability in multivariate normal distribution
• On some entropy and divergence type measures of variability and dependence for mixed continuous and discrete variables
• On the errors of misclassification based on dichotomous and normal variables
• Tests for standardized generalized variances of multivariate normal populations of possibly different dimensions
• Informational distances and related statistics in mixed continuous and categorical variables
• Consistency property of elliptical probability density functions
• An asymptotic test of independence for multivariate \(t\) and Cauchy random variables with applications
• A measure of total variability for the multivariate \(t\) distribution with applications to finance
• Descriptive measures of multivariate scatter and linear dependence
• Expressions for Rényi and Shannon entropies for multivariate distributions
• On maximum entropy characterization of Pearson's type II and VII multivariate distributions
• Generalization of the Mahalanobis distance in the mixed case
• On Mardia's and Song's measures of kurtosis in elliptical distributions
• Measuring stochastic dependence using \(\phi\)-divergence
• Stochastic ordering of bivariate elliptical distributions
• On measures of dependence
• One-Sample Likelihood Ratio Tests for Mixed Data
• TESTS OF HYPOTHESES FOR THE DISTANCE BETWEEN POPULATIONS ON THE MIXTURE OF CATEGORICAL AND CONTINUOUS VARIABLES
• Distance between populations using mixed continuous and categorical variables
• Relative Entropy Measures of Multivariate Dependence
• Discrimination and Classification Using Both Binary and Continuous Variables
• Some linear transformations for mixtures of binary and continuous variables, with particular reference to linear discriminant analysis
• Asymptotic distributions of functions of a sample covariance matrix under the elliptical distribution
• DISTANCE BETWEEN POPULATIONS IN A MIXTURE OF CATEGORICAL AND CONTINUOUS VARIABLES
• On the one-sample location hypothesis for mixed bivariate data
• On diversity measures based on entropy functions
• Dimensionless Measures of Variability and Dependence for Multivariate Continuous Distributions
• Multivariate Two Sample Tests with Dichotomous and Continuous Variables. I. The Location Model
• Multivariate Correlation Models with Mixed Discrete and Continuous Variables
• Statistical classification with quadratic forms
• Rényi information, loglikelihood and an intrinsic distribution measure

This page was built for publication: On some entropy and divergence type measures of variability and dependence for mixed continuous and discrete variables