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pencopulaCond (version 0.2)
Estimating Non-Simplified Vine Copulas Using Penalized Splines
Description
Estimating Non-Simplified Vine Copulas Using Penalized Splines.
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Version
Version
0.2
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Install
install.packages('pencopulaCond')
Monthly Downloads
136
Version
0.2
License
GPL (>= 2)
Maintainer
Christian Schellhase
Last Published
May 31st, 2017
Functions in pencopulaCond (0.2)
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hierarch.bs
Construction of the hierarchical B-spline density basis.
knots.start
Calculating the knots.
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
cal.Dvine
Estimating Non-Simplified Vine Copulas Using Penalized Splines
cal.vine
Estimating Non-Simplified Vine Copulas Using Penalized Splines
Derv2
Calculating the second order derivative with and without penalty.
marg.likelihood
Calculating the marginal likelihood
my.IC
Calculating the AIC-value
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)
Derv1
Calculating the first derivative of the pencopula likelihood function w.r.t. parameter b
my.bspline
my.bspline
my.loop
Iterative loop for calculating the optimal coefficients 'b'.
pendenForm
Formula interpretation and data transfer
plot.pencopula
Plot the estimated copula density or copula distribution.
pencopula
Calculating penalized (conditional) copula density with penalized hierarchical B-splines
pencopulaCond-package
Estimating Non-Simplified Vine Copulas Using Penalized Splines
print.pencopula
Printing the main results of the penalized copula density estimation
vine
"Estimating Non-Simplified Vine Copulas Using Penalized Splines"