Continuous and discrete variables with a copula?

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SUMMARY

This discussion confirms that continuous and discrete variables can be modeled together using a copula function, as established by Sklar's theorem and its converse. The user has three correlated variables, two of which are continuous and one discrete, and seeks clarification on the compatibility of these variable types within a copula framework. The answer provided is a definitive "Yes," affirming the applicability of copulas in this context.

PREREQUISITES
  • Understanding of copula functions
  • Familiarity with Sklar's theorem
  • Knowledge of continuous and discrete variable types
  • Basic statistical modeling concepts
NEXT STEPS
  • Study the application of Sklar's theorem in statistical modeling
  • Explore different types of copulas, such as Gaussian and Clayton copulas
  • Learn about the implications of modeling mixed variable types in copulas
  • Investigate software tools for implementing copula models, such as R's 'copula' package
USEFUL FOR

Statisticians, data scientists, and researchers interested in advanced statistical modeling techniques involving mixed variable types, particularly those utilizing copulas.

bradyj7
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Hi,

I have 3 correlated variables that I wish to model with a copula function. 2 of the variables are continuous and 1 is discrete.

My question is, generally speaking can you model continuous and discrete variables within the same copula? Yes/No?

Thanks
 
Physics news on Phys.org
Yes - Sklar's theorem and its converse still applies.
 

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