reduce

<code>reduce</code> reports the count of non-zero elements, sum and sum-of-squares for specified covariates in a Cyclops data object.

internal

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 

reduce function

<dl><dt>object</dt>
<dd>A Cyclops data object</dd>
<dt>covariates</dt>
<dd>Integer or string vector: list of covariates to report</dd>
<dt>groupBy</dt>
<dd>Integer or string (optional): generates a segmented reduction stratified by this covariate. Setting <code>groupBy = "stratum"</code> segments reduction for strataID</dd>
<dt>power</dt>
<dd>Integer: 0 = non-zero count, 1 = sum, 2 = sum-of-squares</dd></dl>

Arguments

Apply simple data reductions — reduce

<dl>

<dt>object</dt>
<dd>A Cyclops data object</dd>


<dt>covariates</dt>
<dd>Integer or string vector: list of covariates to report</dd>


<dt>groupBy</dt>
<dd>Integer or string (optional): generates a segmented reduction stratified by this covariate. Setting <code>groupBy = "stratum"</code> segments reduction for strataID</dd>


<dt>power</dt>
<dd>Integer: 0 = non-zero count, 1 = sum, 2 = sum-of-squares</dd>

</dl>

Apply simple data reductions

reduce: Apply simple data reductions

Description

Usage

Value

Arguments