feasible_point_search {depCensoring} | R Documentation |
Method for finding initial points of the EAM algorithm
Description
Also called the 'initialization' step in KMS19, this method tries to find at least one initial feasible point, which is required to run the EAM algorithm. ToDo: Investigate whether the feasible point search of Bei (2024) is better. If so, implement it.
Usage
feasible_point_search(
test.fun,
hyperparams,
verbose,
picturose = FALSE,
parallel = FALSE
)
Arguments
test.fun |
Function that takes a parameter vector as a first argument and returns the test statistic, as well as the critical value. |
hyperparams |
List of hyperparameters. |
verbose |
Verbosity parameter. |
picturose |
Picturosity flag. If |
parallel |
Flag for whether or not parallel computing should be used.
Default is |
Value
Results of the initial feasible point search.
References
Kaido et al. (2019). Confidence intervals for projections of partially identified parameters. Econometrica. 87(4):1397-1432.