Generates correlated random samples using various copula models (Gaussian, Student-t, Clayton, Frank, Gumbel, Joe). Copulas model dependency structures between variables while preserving marginal distributions. Essential for multivariate risk modeling, credit portfolio modeling, and Monte Carlo simulations where correlation matters. [Tier: PRO, Credits: 5]
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Type of copula to use
gaussian, student_t, clayton, frank, gumbel, joe "student_t"
Correlation parameter (for Gaussian/Student-t) or theta parameter (for Archimedean copulas)
-0.99 <= x <= 0.990.5
Degrees of freedom for Student-t copula (required if copula_type is student_t)
x >= 25
Number of samples to generate
x >= 1001000
Random seed for reproducibility
42