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| rvinecopulib-package | High Performance Algorithms for Vine Copula Modeling |
| bicop | Bivariate copula models |
| bicop_dist | Bivariate copula models |
| bicop_distributions | Bivariate copula distributions |
| bicop_predict_and_fitted | Predictions and fitted values for a bivariate copula model |
| check_rvine_matrix | R-vine matrices |
| contour.bicop | Plotting tools for 'bicop_dist' and 'bicop' objects |
| contour.bicop_dist | Plotting tools for 'bicop_dist' and 'bicop' objects |
| contour.vinecop | Plotting 'vinecop_dist' and 'vinecop' objects. |
| contour.vinecop_dist | Plotting 'vinecop_dist' and 'vinecop' objects. |
| dbicop | Bivariate copula distributions |
| dbicop_dist | Bivariate copula distributions |
| dvinecop | Vine copula distributions |
| dvinecop_dist | Vine copula distributions |
| fitted.bicop | Predictions and fitted values for a bivariate copula model |
| fitted.vinecop | Predictions and fitted values for a vine copula model |
| hbicop | Bivariate copula distributions |
| hbicop_dist | Bivariate copula distributions |
| mBICV | calculates the vine copula Bayesian information criterion (vBIC), which is defined as \mathrm{BIC} = -2\, \mathrm{loglik} + nu \ln(n), - 2 * sum_{t=1}^(d - 1) \{q_t log(psi_0^t) - (d - t - q_t) log(1 - psi_0^t)\} where \mathrm{loglik} is the log-liklihood and nu is the (effective) number of parameters of the model, t is the tree level psi_0 is the prior probability of having a non-independence copula and q_t is the number of non-independence copulas in tree t. The vBIC is a consistent model selection criterion for parametric sparse vine copula models. |
| par_to_tau | Conversion between Kendall's tau and parameters |
| pbicop | Bivariate copula distributions |
| pbicop_dist | Bivariate copula distributions |
| plot.bicop | Plotting tools for 'bicop_dist' and 'bicop' objects |
| plot.bicop_dist | Plotting tools for 'bicop_dist' and 'bicop' objects |
| plot.vinecop | Plotting 'vinecop_dist' and 'vinecop' objects. |
| plot.vinecop_dist | Plotting 'vinecop_dist' and 'vinecop' objects. |
| predict.bicop | Predictions and fitted values for a bivariate copula model |
| predict.vinecop | Predictions and fitted values for a vine copula model |
| pvinecop | Vine copula distributions |
| pvinecop_dist | Vine copula distributions |
| rbicop | Bivariate copula distributions |
| rbicop_dist | Bivariate copula distributions |
| rvinecop | Vine copula distributions |
| rvinecopulib | High Performance Algorithms for Vine Copula Modeling |
| rvinecop_dist | Vine copula distributions |
| tau_to_par | Conversion between Kendall's tau and parameters |
| vinecop | Vine copula models |
| vinecop_dist | Vine copula models |
| vinecop_distributions | Vine copula distributions |
| vinecop_predict_and_fitted | Predictions and fitted values for a vine copula model |