combine_times

internal

Based on random forest principle, 'DynForest' is able to include
multiple longitudinal predictors to provide individual predictions.
Longitudinal predictors are modeled through the random forest. The
methodology is fully described for a survival outcome in:
Devaux, Helmer, Genuer & Proust-Lima (2023)
<doi: 10.1177/09622802231206477>.

Anthony Devaux

DynForest

Random Forest with Multivariate Longitudinal Predictors

Robin Genuer

Cécile Proust-Lima

Louis Capitaine

combine_times function

<dl><dt>pred</dt>
<dd>Prediction matrix</dd>
<dt>newtimes</dt>
<dd>Numeric vector of new times</dd>
<dt>type</dt>
<dd>Character indicating survival function (<code>type</code>="surv") or risk function (<code>type</code>="risk")</dd></dl>

Arguments

Extend predictions for new times — combine_times

<dl>

<dt>pred</dt>
<dd>Prediction matrix</dd>


<dt>newtimes</dt>
<dd>Numeric vector of new times</dd>


<dt>type</dt>
<dd>Character indicating survival function (<code>type</code>="surv") or risk function (<code>type</code>="risk")</dd>

</dl>

Extend predictions for new times

combine_times: Extend predictions for new times

Description

Usage

Arguments