predict.cyclopsFit

<code>predict.cyclopsFit</code> computes model response-scale predictive values for all data rows

This model fitting tool incorporates cyclic coordinate descent and
majorization-minimization approaches to fit a variety of regression models
found in large-scale observational healthcare data. Implementations focus
on computational optimization and fine-scale parallelization to yield
efficient inference in massive datasets. Please see:
Suchard, Simpson, Zorych, Ryan and Madigan (2013) <doi:10.1145/2414416.2414791>.

Marc A Suchard

Cyclops

Cyclic Coordinate Descent for Logistic, Poisson and Survival
Analysis

Marc A. Suchard

Martijn J. Schuemie

Trevor R. Shaddox

Yuxi Tian

Jianxiao Yang

Eric Kawaguchi

Sushil Mittal

Observational Health Data Sciences and Informatics 

Marcus Geelnard

Rutgers University 

R Development Core Team 

predict.cyclopsFit function

<dl><dt>object</dt>
<dd>A Cyclops model fit object</dd>
<dt>newOutcomes</dt>
<dd>An optional data frame or Andromeda table object, similar to the object used in <code>convertToCyclopsData</code>.</dd>
<dt>newCovariates</dt>
<dd>An optional data frame or Andromeda table object, similar to the object used in <code>convertToCyclopsData</code>.</dd>
<dt>...</dt>
<dd>Additional arguments</dd></dl>

Arguments

Model predictions — predict.cyclopsFit

<dl>

<dt>object</dt>
<dd>A Cyclops model fit object</dd>


<dt>newOutcomes</dt>
<dd>An optional data frame or Andromeda table object, similar to the object used in <code>convertToCyclopsData</code>.</dd>


<dt>newCovariates</dt>
<dd>An optional data frame or Andromeda table object, similar to the object used in <code>convertToCyclopsData</code>.</dd>


<dt>...</dt>
<dd>Additional arguments</dd>

</dl>

Model predictions

predict.cyclopsFit: Model predictions

Description

Usage

Arguments