| kdecopula-package | Kernel Smoothing for Bivariate Copula Densities |
| bw_bern | Bandwidth selection for the Bernstein copula estimator |
| bw_beta | Bandwidth selection for the beta kernel estimator |
| bw_mr | Bandwidth selection for the mirror-reflection estimator |
| bw_t | Bandwidth selection for the transformation kernel estimator |
| bw_tll | Bandwidth selection for the transformation local likelihood estimator |
| bw_tll_nn | Nearest-neighbor bandwidth selection for the transformation local likelihood estimator |
| bw_tt_cv | Nearest-neighbor bandwidth selection for the tapered transformation estimator |
| bw_tt_pi | Nearest-neighbor bandwidth selection for the tapered transformation estimator |
| contour.kdecopula | Plotting 'kdecopula' objects |
| dep_measures | Dependence measures of a 'kdecop()' fit |
| dkdecop | Working with 'kdecopula' objects |
| fitted.kdecopula | Extract fitted values from a 'kdecop()' fits. |
| hkdecop | H-function and inverse of a 'kdecop()' fit |
| kdecop | Bivariate kernel copula density estimation |
| kdecopula | Kernel Smoothing for Bivariate Copula Densities |
| logLik.kdecopula | Log-Likelihood of a 'kdecopula' object |
| pkdecop | Working with 'kdecopula' objects |
| plot.kdecopula | Plotting 'kdecopula' objects |
| predict.kdecopula | Prediction method for 'kdecop()' fits |
| rkdecop | Working with 'kdecopula' objects |
| simulate.kdecopula | Simulate data from a 'kdecop()' fit. |
| wdbc | Wisconsin Diagnostic Breast Cancer (WDBC) |