E_step

This function performs the estimation step in the EAM algorithm.

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

E_step function

<dl><dt>thetas</dt>
<dd>Points at which to perform the E-step. Usually the result of
the M-step.</dd>
<dt>test.fun</dt>
<dd>Function returning the test statistic, as well as the critical
value.</dd>
<dt>dir</dt>
<dd>Direction in which to optimize. For finding upper bounds, set
<code>dir = 1</code>, for finding lower bounds, set <code>dir = -1</code>.</dd>
<dt>evaluations</dt>
<dd>Matrix containing each point that was already evaluated,
alongside the corresponding test statistic and critical value, as its rows.</dd>
<dt>verbose</dt>
<dd>Verbosity parameter.</dd></dl>

Arguments

E-step in the EAM algorithm as described in KMS19. — E_step

<dl>

<dt>thetas</dt>
<dd>Points at which to perform the E-step. Usually the result of
the M-step.</dd>


<dt>test.fun</dt>
<dd>Function returning the test statistic, as well as the critical
value.</dd>


<dt>dir</dt>
<dd>Direction in which to optimize. For finding upper bounds, set
<code>dir = 1</code>, for finding lower bounds, set <code>dir = -1</code>.</dd>


<dt>evaluations</dt>
<dd>Matrix containing each point that was already evaluated,
alongside the corresponding test statistic and critical value, as its rows.</dd>


<dt>verbose</dt>
<dd>Verbosity parameter.</dd>

</dl>

E_step: E-step in the EAM algorithm as described in KMS19.

Description

Usage

Value

Arguments