gs.algo.bidir

This function implements a rudimentary, bidirectional search algorithm. It
works by expanding a grid with given step.size in both directions, starting
from an initial feasible point.

Several statistical methods for analyzing survival data under various forms of dependent
censoring are implemented in the package. In addition to accounting for dependent censoring, it
offers tools to adjust for unmeasured confounding factors. The implemented approaches allow
users to estimate the dependency between survival time and dependent censoring time, based
solely on observed survival data. For more details on the methods, refer to Deresa and Van
Keilegom (2021) <doi:10.1093/biomet/asaa095>, Czado and Van Keilegom (2023)
<doi:10.1093/biomet/asac067>, Crommen et al. (2024) <doi:10.1007/s11749-023-00903-9>,
Deresa and Van Keilegom (2024) <doi:10.1080/01621459.2022.2161387>, Rutten et al. (2024+)
<doi:10.48550/arXiv.2403.11860> and Ding and Van Keilegom (2024).

Negera Wakgari Deresa

depCensoring

Statistical Methods for Survival Data with Dependent Censoring

Ilias Willems

Gilles Crommen

Jie Ding

Claudia Czado

Ingrid Van Keilegom

gs.algo.bidir function

<dl><dt>test.results</dt>
<dd>Matrix containing the evaluations of the test statistic
and critical value.</dd>
<dt>max.iter</dt>
<dd>Maximum number of iterations.</dd>
<dt>step.size</dt>
<dd>Step size based on which the grid is constructed.</dd></dl>

Arguments

Rudimentary, bidirectional 1D grid search algorithm. — gs.algo.bidir

<dl>

<dt>test.results</dt>
<dd>Matrix containing the evaluations of the test statistic
and critical value.</dd>


<dt>max.iter</dt>
<dd>Maximum number of iterations.</dd>


<dt>step.size</dt>
<dd>Step size based on which the grid is constructed.</dd>

</dl>

gs.algo.bidir: Rudimentary, bidirectional 1D grid search algorithm.

Description

Usage

Value

Arguments