Dvine_ICA_confint() computes the confidence interval for the ICA
in the D-vine copula model. The unidentifiable parameters are fixed at the user
supplied values.
Dvine_ICA_confint(
fitted_model,
alpha,
copula_par_unid,
copula_family2,
rotation_par_unid,
n_prec,
mutinfo_estimator = NULL,
composite,
B,
seed
)(numeric) Vector with the limits of the two-sided 1 - alpha
confidence interval.
Returned value from fit_model_SurvSurv(). This object
contains the estimated identifiable part of the joint distribution for the
potential outcomes.
(numeric) 1 - alpha is the level of the confidence interval
Parameter vector for the sequence of unidentifiable
bivariate copulas that define the D-vine copula. The elements of
copula_par correspond to \((c_{23}, c_{13;2}, c_{24;3}, c_{14;23})\).
Copula family of the other bivariate copulas. For the
possible options, see loglik_copula_scale(). The elements of
copula_family2 correspond to \((c_{23}, c_{13;2}, c_{24;3}, c_{14;23})\).
Vector of rotation parameters for the sequence of
unidentifiable bivariate copulas that define the D-vine copula. The elements of
rotation_par correspond to \((c_{23}, c_{13;2},
c_{24;3}, c_{14;23})\).
Number of Monte Carlo samples for the computation of the mutual information.
Function that estimates the mutual information
between the first two arguments which are numeric vectors. Defaults to
FNN::mutinfo() with default arguments.
(boolean) If composite is TRUE, then the surrogate
endpoint is a composite of both a "pure" surrogate endpoint and the true
endpoint, e.g., progression-free survival is the minimum of time-to-progression
and time-to-death.
Number of bootstrap replications
Seed for Monte Carlo sampling. This seed does not affect the global environment.