check.args.pisurv: Check argument consistency.

Description

This function checks whether the arguments supplied to the main estimation function pi.surv are valid. When arguments are invalid, the an exception is thrown.

Usage

check.args.pisurv(
  data,
  idx.param.of.interest,
  idxs.c,
  t,
  par.space,
  search.method,
  add.options
)

Arguments

data: Data frame containing the data on which to fit the model. The columns should be named as follows: 'Y' = observed timed, 'Delta' = censoring indicators, 'X0' = intercept column, 'X1' - 'Xp' = covariates.
idx.param.of.interest: Index of element in the covariate vector for which the identified interval should be estimated. It can also be specified as idx.param.of.interest = "all", in which case identified intervals will be computed for all elements in the parameter vector. Note that idx.param.of.interest = 1 corresponds to the intercept parameter.
idxs.c: Vector of indices of the continuous covariates. Suppose the given data contains 5 covariates, of which 'X2' and 'X5' are continuous, this argument should be specified as idxs.c = c(2, 5).
t: Time point for which to estimate the identified set of \(\beta(t)\).
par.space: Matrix containing bounds on the space of the parameters. The first column corresponds to lower bounds, the second to upper bounds. The i'th row corresponds to the bounds on the i'th element in the parameter vector.
search.method: The search method to be used to find the identified interval. Default is search.method = "GS".
add.options: List of additional options to be specified to the method. Notably, it can be used to select the link function \(\Lambda(t))\) that should be considered. Currently, the link function leading to an accelerated failure time model ("AFT_ll", default) and the link function leading to a Cox proportional hazards model ("Cox_wb") are implemented. Other options can range from 'standard' hyperparameters such as the confidence level of the test and number of instrumental functions to be used, to technical hyperparameters regarding the search method and test implementation. For the latter, we refer to the documentations of set.hyperparameters, set.EAM.hyperparameters and set.GS.hyperparameters. We recommend to use the default parameters, unless you really know what you are doing.