ICA_given_model_constructor: Constructor for the function that returns that ICA as a function of the identifiable parameters

Description

ICA_given_model_constructor() returns a function fixes the unidentifiable parameters at user-specified values and takes the identifiable parameters as argument.

Usage

ICA_given_model_constructor(
  fitted_model,
  copula_par_unid,
  copula_family2,
  rotation_par_unid,
  n_prec,
  measure = "ICA",
  mutinfo_estimator = NULL,
  ICA_estimator = NULL,
  seed,
  composite = NULL,
  restr_time = +Inf
)

Value

A function that computes the ICA as a function of the identifiable parameters. In this computation, the unidentifiable parameters are fixed at the values supplied as arguments to ICA_given_model_constructor_SurvSurv() or ICA_given_model_constructor().

Arguments

fitted_model: Returned value from fit_copula_OrdOrd(), fit_copula_OrdCont(), or fit_copula_ContCont(). This object contains the estimated identifiable part of the joint distribution for the potential outcomes.
copula_par_unid: 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_family2: Copula family of the other bivariate copulas. For the possible options, see loglik_copula_scale(). The elements of copula_family2 correspond to \((c_{23}, c_{13;2}, c_{24;3}, c_{14;23})\).
rotation_par_unid: Vector of rotation parameters for the sequence of unidentifiable bivariate copulas that define the D-vine copula. The elements of rotation_par correspond to \((c_{23}, c_{13;2}, c_{24;3}, c_{14;23})\).
n_prec: Number of Monte Carlo samples for the computation of the mutual information.
measure: Compute intervals for which measure of surrogacy? Defaults to "ICA". See first column names of sens_results for other possibilities.
mutinfo_estimator: Function that estimates the mutual information between the first two arguments which are numeric vectors. Defaults to FNN::mutinfo() with default arguments in the survival-survival setting. This argument is not used for non-survival-survival settings.
ICA_estimator: Function that estimates the ICA between the first two arguments which are numeric vectors. Defaults to NULL which corresponds to using estimate_ICA_ContCont(), estimate_ICA_OrdCont(), or estimate_ICA_OrdOrd() (depending on the endpoint types). This argument is not used in the survival-survival setting.
seed: Seed for Monte Carlo sampling. This seed does not affect the global environment.
composite: (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.
restr_time: Restriction time for the potential outcomes. Defaults to +Inf which means no restriction. Otherwise, the sampled potential outcomes are replace by pmin(S0, restr_time) (and similarly for the other potential outcomes).