Copula Distributions and Correlated Samples
Fit parameters of a model of correlated random samples to data, evaluate the distribution, generate serially correlated pseudorandom samples
|Copula cumulative distribution function|
|Copula probability density function|
|Copula parameters as function of rank correlation|
|Copula rank correlation|
|Fit copula to data|
|Copula random numbers|
- 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.