Compute correlated random numbers according to Gaussian or Student-t copulas and
arbitrary marginal distributions within the Pearson distribution system.
Variables:
- corr_matrix: Correlation matrix
- P: matrix with statistical parameter (columns: risk factors,
rows: four moments of distribution (mean, std, skew, kurt)
- mc: number of MC scenarios
- copulatype: t, Gaussian or Frank, Gumbel, Clayton (FGC)
- nu: degree of freedom (scalar for t, scalar or vector for FGC)
- time_horizon: time horizon in days (assumed 256 days in year)
- path_static: path to static files (e.g. random numbers)
- para_object: object with parameters (stable_seed, use_sobol,
sobol_seed, path_working_folder, path_sobol_direction_number,
filename_sobol_direction_number,frob_norm_limit)
- R: OUTPUT: scenario matrix (rows: scenarios, cols: risk factors)
- distr_type: OUTPUT: cell with marginal distribution types
- Z: OUTPUT: copula dependence (uniform marginal distributions)
according to Pearson
See also: get_marginal_distr_pearson, mvnrnd, normcdf, mvtrnd ,tcdf.