Estimating Non-Simplified Vine Copulas Using Penalized Splines

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Documentation for package ‘pencopulaCond’ version 0.2

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pencopulaCond-package Estimating Non-Simplified Vine Copulas Using Penalized Splines
cal.Dvine Estimating Non-Simplified Vine Copulas Using Penalized Splines
cal.vine Estimating Non-Simplified Vine Copulas Using Penalized Splines
Derv1 Calculating the first derivative of the pencopula likelihood function w.r.t. parameter b
Derv2 Calculating the second order derivative with and without penalty.
distr.func.help These functions are used for calculating the integral of the B-spline density basis.
f.hat.val Calculating the actual fitted values 'f.hat.val' of the estimated density function
hierarch.bs Construction of the hierarchical B-spline density basis.
int.my.bspline my.bspline
knots.order Calculating the knots.
knots.start Calculating the knots.
knots.transform Calculating the knots.
marg.likelihood Calculating the marginal likelihood
my.bspline my.bspline
my.IC Calculating the AIC-value
my.loop Iterative loop for calculating the optimal coefficients 'b'.
my.positive.definite.solve my.positive.definite.solve
new.weights Calculating new weights b.
pen.log.like Calculating the log likelihood
penalty.matrix Calculating the penalty matrix P(lambda)
pencopula Calculating penalized (conditional) copula density with penalized hierarchical B-splines
pendenForm Formula interpretation and data transfer
plot.pencopula Plot the estimated copula density or copula distribution.
poly.part These functions are used for calculating the integral of the B-spline density basis.
print Printing the main results of the penalized copula density estimation
print.pencopula Printing the main results of the penalized copula density estimation
vine "Estimating Non-Simplified Vine Copulas Using Penalized Splines"