performParallelNLMERun

Runs a set of NLME jobs in parallel

Perform Nonlinear Mixed-Effects (NLME) Modeling using Certara's
NLME-Engine. Access the same Maximum Likelihood engines used in the Phoenix
platform, including algorithms for parametric methods, individual, and pooled
data analysis <https://www.certara.com/app/uploads/2020/06/BR_PhoenixNLME-v4.pdf>.
The Quasi-Random Parametric Expectation-Maximization Method (QRPEM) is also
supported <https://www.page-meeting.org/default.asp?abstract=2338>. Execution
is supported both locally or on remote machines. Remote execution includes
support for Linux Sun Grid Engine (SGE), Terascale Open-source Resource and
Queue Manager (TORQUE) grids, Linux and Windows multicore, and individual runs.

James Craig

Certara.NLME8

Utilities for Certara's Nonlinear Mixed-Effects Modeling Engine

Soltanshahi Fred

Michael Tomashevskiy

Shuhua Hu

Certara USA, Inc. 

performParallelNLMERun function

<dl><dt>args</dt>
<dd>a vector of arguments provided as the following:
c(jobType, parallelMethod, install_dir, shared_directory,
localWorkingDir, controlFile, NumProc, workflow_name, fixefUnits)</dd>
<dt>partialJob</dt>
<dd>is <code>TRUE</code> if it is not required to stop the job
as for covariate stepwise search</dd>
<dt>allowIntermediateResults</dt>
<dd>is <code>TRUE</code> if intermediate results
are possible like for sorting</dd>
<dt>progressStage</dt>
<dd>stage of analysis to be reported</dd>
<dt>func</dt>
<dd>function to be executed after NLME job</dd>
<dt>func_arg</dt>
<dd>arguments to be provided to the function by name provided above</dd>
<dt>reportProgress</dt>
<dd>whether it is required to report the progress
(for local jobs usually)</dd></dl>

Arguments

Runs a set of NLME jobs in parallel — performParallelNLMERun

<dl>

<dt>args</dt>
<dd>a vector of arguments provided as the following:
c(jobType, parallelMethod, install_dir, shared_directory,
localWorkingDir, controlFile, NumProc, workflow_name, fixefUnits)</dd>


<dt>partialJob</dt>
<dd>is <code>TRUE</code> if it is not required to stop the job
as for covariate stepwise search</dd>


<dt>allowIntermediateResults</dt>
<dd>is <code>TRUE</code> if intermediate results
are possible like for sorting</dd>


<dt>progressStage</dt>
<dd>stage of analysis to be reported</dd>


<dt>func</dt>
<dd>function to be executed after NLME job</dd>


<dt>func_arg</dt>
<dd>arguments to be provided to the function by name provided above</dd>


<dt>reportProgress</dt>
<dd>whether it is required to report the progress
(for local jobs usually)</dd>

</dl>

performParallelNLMERun: Runs a set of NLME jobs in parallel

Description

Usage

Value

Arguments