Estimating Non-Simplified Vine Copulas Using Penalized Splines
Estimating Non-Simplified Vine Copulas Using Penalized Splines
Estimating Non-Simplified Vine Copulas Using Penalized Splines
Calculating the first derivative of the pencopula likelihood function ...
Calculating the second order derivative with and without penalty.
These functions are used for calculating the integral of the B-spline ...
Calculating the actual fitted values 'f.hat.val' of the estimated dens...
Construction of the hierarchical B-spline density basis.
Calculating the knots.
Calculating the marginal likelihood
my.bspline
Calculating the AIC-value
Iterative loop for calculating the optimal coefficients 'b'.
my.positive.definite.solve
Calculating new weights b.
Calculating the log likelihood
Calculating the penalty matrix P(lambda)
Calculating penalized (conditional) copula density with penalized hier...
Estimating Non-Simplified Vine Copulas Using Penalized Splines
Formula interpretation and data transfer
Plot the estimated copula density or copula distribution.
Printing the main results of the penalized copula density estimation
"Estimating Non-Simplified Vine Copulas Using Penalized Splines"
Estimating Non-Simplified Vine Copulas Using Penalized Splines.