Containing all information, environment of
paircopula().
temp
Default=FALSE,if TRUE temporary calculations of
optimal parameters are done.
lambda
Default=NULL, i.e. the saved smoothing parameter lambda in the
environment is used. Alternatively, temporary values of lambda
are used for optimization of lambda.
lam.fit
Default=FALSE, indicating if the first derivative is calculated to determine the next optimal penalty parameter lambda.
Value
Derv1.pen
first order derivation of the penalized likelihood
function w.r.t. parameter v.
Derv1.pen is saved in the environment.
Details
The calculation of the first derivative of the paircopula likelihood function w.r.t. b equals
$$s(v,\lambda)= {\partial l(v,\lambda)}/{\partial v}= \sum_{i=1}^n
\Phi(u_i)/c(u_i,v) - P(\lambda)v$$
with $$P(\lambda)$$
is the penalty matrix, saved in the environment.
References
Flexible Pair-Copula Estimation in D-vines using Bivariate Penalized
Splines, Kauermann, G. and Schellhase, C. (2014), Statistics and Computing 24(6): 1081-1100).
Nonparametric estimation of simplified vines: comparison of methods, Nagler N., Schellhase, C. and Czado, C. (2017) Dependence Modeling.