brier

Computes the Brier score at a fixed time point using inverse probability of censoring weights (IPCW).

Provides deep learning models for right-censored survival data using the 'torch' backend.
Supports multiple loss functions, including Cox partial likelihood, L2-penalized Cox, time-dependent Cox,
and accelerated failure time (AFT) loss. Offers a formula-based interface, built-in support for cross-validation,
hyperparameter tuning, survival curve plotting, and evaluation metrics such as the C-index, Brier score,
and integrated Brier score. For methodological details, see Kvamme et al. (2019) <https://www.jmlr.org/papers/v20/18-424.html>.

Imad El Badisy

survdnn

Deep Neural Networks for Survival Analysis Using 'torch'

Imad EL BADISY

brier function

<dl><dt>object</dt>
<dd>A `Surv` object with observed time and status.</dd>
<dt>pre_sp</dt>
<dd>A numeric vector of predicted survival probabilities at `t_star`.</dd>
<dt>t_star</dt>
<dd>The evaluation time point.</dd></dl>

Arguments

Brier Score for Right-Censored Survival Data at a Fixed Time — brier

<dl>

<dt>object</dt>
<dd>A `Surv` object with observed time and status.</dd>


<dt>pre_sp</dt>
<dd>A numeric vector of predicted survival probabilities at `t_star`.</dd>


<dt>t_star</dt>
<dd>The evaluation time point.</dd>

</dl>

brier: Brier Score for Right-Censored Survival Data at a Fixed Time

Description

Usage

Value

Arguments

Examples