get.dmi.tens

This function provides a faster implementation of obtaining the
evaluations of the derivative of the moment functions at each observation
(wrt the previous implementation using 'dm.comp' and 'dm.R'). Used in the
function G.hat.R

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

get.dmi.tens function

<dl><dt>data</dt>
<dd>Data frame.</dd>
<dt>beta</dt>
<dd>Vector of coefficients.</dd>
<dt>t</dt>
<dd>Time point of interest. Also allowed to
be a vector of time points (used in estimating the model under assumed time-
independent coefficients).</dd>
<dt>hp</dt>
<dd>List of hyperparameters.</dd>
<dt>inst.func.evals</dt>
<dd>Precomputed matrix of instrumental function
evaluations. Defaults is <code>inst.func.evals = NULL</code>, in which case the
evaluations will be done inside this function.</dd></dl>

Arguments

Faster implementation to obtain the tensor of the evaluations of the
derivatives of the moment functions at each observation. — get.dmi.tens

<dl>

<dt>data</dt>
<dd>Data frame.</dd>


<dt>beta</dt>
<dd>Vector of coefficients.</dd>


<dt>t</dt>
<dd>Time point of interest. Also allowed to
be a vector of time points (used in estimating the model under assumed time-
independent coefficients).</dd>


<dt>hp</dt>
<dd>List of hyperparameters.</dd>


<dt>inst.func.evals</dt>
<dd>Precomputed matrix of instrumental function
evaluations. Defaults is <code>inst.func.evals = NULL</code>, in which case the
evaluations will be done inside this function.</dd>

</dl>

get.dmi.tens: Faster implementation to obtain the tensor of the evaluations of the derivatives of the moment functions at each observation.

Description

Usage

Arguments