predict.big_pls_cox_fast

Predictions for fast big PLS–Cox fits

Provides Partial least squares Regression and various regular, sparse
or kernel, techniques for fitting Cox models for big data. Provides a Partial
Least Squares (PLS) algorithm adapted to Cox proportional hazards models that
works with 'bigmemory' matrices without loading the entire dataset in memory.
Also implements a gradient-descent based solver for Cox proportional hazards
models that works directly on 'bigmemory' matrices.
Bertrand and Maumy (2023) <https://hal.science/hal-05352069>, and
<https://hal.science/hal-05352061> highlighted
fitting and cross-validating PLS-based Cox models to censored big data.

Frederic Bertrand

bigPLScox

Partial Least Squares for Cox Models with Big Matrices

Myriam Maumy-Bertrand

predict.big_pls_cox_fast function

<dl><dt>object</dt>
<dd>An object of class <code>"big_pls_cox_fast"</code>.</dd>
<dt>newdata</dt>
<dd>Optional matrix or <code>big.matrix</code> with predictors.</dd>
<dt>type</dt>
<dd>Type of prediction: <code>"link"</code>, <code>"risk"</code>,
<code>"response"</code>, or <code>"components"</code>.</dd>
<dt>comps</dt>
<dd>Optional components to use. Defaults to all.</dd>
<dt>coef</dt>
<dd>Optional coefficient vector. Defaults to <code>object$coefficients</code>.</dd>
<dt>...</dt>
<dd>Ignored.</dd></dl>

Arguments

Predictions for fast big PLS–Cox fits — predict.big_pls_cox_fast

<dl>

<dt>object</dt>
<dd>An object of class <code>"big_pls_cox_fast"</code>.</dd>


<dt>newdata</dt>
<dd>Optional matrix or <code>big.matrix</code> with predictors.</dd>


<dt>type</dt>
<dd>Type of prediction: <code>"link"</code>, <code>"risk"</code>,
<code>"response"</code>, or <code>"components"</code>.</dd>


<dt>comps</dt>
<dd>Optional components to use. Defaults to all.</dd>


<dt>coef</dt>
<dd>Optional coefficient vector. Defaults to <code>object$coefficients</code>.</dd>


<dt>...</dt>
<dd>Ignored.</dd>

</dl>

predict.big_pls_cox_fast: Predictions for fast big PLS–Cox fits

Description

Usage

Arguments