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Copula Distributions and Correlated Samples

Fit parameters of a model of correlated random samples to data, evaluate the distribution, generate serially correlated pseudorandom samples

Functions

copulacdfCopula cumulative distribution function
copulapdfCopula probability density function
copulaparamCopula parameters as function of rank correlation
copulastatCopula rank correlation
copulafitFit copula to data
copularndCopula random numbers

Topics

Copulas: Generate Correlated Samples

Copulas are functions that describe dependencies among variables, and provide a way to create distributions that model correlated multivariate data.

Generate Correlated Data Using Rank Correlation

This example shows how to use a copula and rank correlation to generate correlated data from probability distributions that do not have an inverse cdf function available, such as the Pearson flexible distribution family.

Simulating Dependent Random Variables Using Copulas

This example shows how to use copulas to generate data from multivariate distributions when there are complicated relationships among the variables, or when the individual variables are from different distributions.