draw.sv.init: Draw initial set of starting values for optimizing the...

In depCensoring: Statistical Methods for Survival Data with Dependent Censoring

Draw initial set of starting values for optimizing the expected improvement.

Description

Used in the M-step (get.starting.values.R). ToDo: Adapt this code so as to also perform sample space contractions as in the MatLab implementation of Bei (2024).

Usage

draw.sv.init(theta.hash, dir, hyperparams, EI.fun)

Arguments

theta.hash	Tentative optimal value for theta, i.e., the largest or smallest feasible value for theta (if dir = 1 or dir = -1, respectively). A 'feasible value' is one that satisfies all moment restrictions.
dir	Search direction. dir = 1 corresponds to looking for an upper bound. dir = -1 corresponds to looking for a lower bound.
hyperparams	List of hyperparameters.
EI.fun	Function used to compute the expected improvement. See also EI.

Value

Initial set of starting values.

References

Bei, X. (2024). Local linearieation based subvector inference in moment inequality models. Journal of Econometrics. 238:105549-

depCensoring documentation built on April 4, 2025, 1:52 a.m.