set.hyperparameters: Define the hyperparameters used for finding the identified interval

Description

This function defines all the necessary hyperparameters used to run the methodology.

Usage

set.hyperparameters(data, par.space, c, search.method, options)

Value

The list of hyperparameters.

Arguments

data

Data frame.

par.space

Bounds on the parameter space.

c

Projection vector.

search.method

Search method to use ("EAM" or "GS")

options

List of user specified hyperparameters that will substitute the corresponding default values. This list can contain the entries:

cov.ranges:: known bounds on each of the covariates in the data set.

norm.func.name:

Name of the normalization function to be used. Can be either "normalize.covariates1" or "normalize.covariates2" (default). The former is a simple elementwise rescaling. The latter uses the PCA approach as discussed in Willems et al. (2024+).

inst.func.family:

Family of instrumental functions to be used for all covariates. Options are "box", "spline" and "cd". The former two are only applicable for continuous covariates. The latter can also handle discrete covariates. Default is "cd".

G.c:

The class of instrumental functions used for the continuous covariates in the model, in case "cd" is selected as inst.func.family:. Options are "box" and "spline". Default is "spline".

degree:

The degree of the B-spline functions, should they be used as instrumental functions for the continuous covariates. Default is 3.

link.function:

Name of the link function to be used. Options are "AFT_ll" for the AFT model with log-logistic baseline, or "Cox_wb" for the Cox PH model (originally with Weibull baseline, but now for a general) baseline hazard).

K.bar:

Number of refinement steps when obtaining the critical value. See Bei (2024).

B:

Number of bootstrap samples to be used when obtaining the bootstrap distribution of the test statistic.

ignore.empty.IF:

Boolean value indicating whether instrumental functions with empty support should be ignored (cf. Willems et al., 2024). Default is FALSE. The feature ignore.empty.IF = TRUE is experimental, so there might exist edge cases for which the implementation will fail to run.

Other (hidden) options can also be overwritten, though we highly discourage this. If necessary, you can consult the source code of this functions to find the names of the desired parameters and add their name alongside their desired value as an entry in options (e.g. options$min.var <- 1e-4. Again, not recommended!).