Version: 3.0.1
Title: Utilities for Certara's Nonlinear Mixed-Effects Modeling Engine
Description: 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.
Depends: R (≥ 4.0.0)
License: LGPL-3
RoxygenNote: 7.3.2
Suggests: testthat
Imports: xml2, batchtools (≥ 0.9.9), reshape, utils, data.table
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-10-15 15:34:12 UTC; jcraig
Author: Soltanshahi Fred [aut], Michael Tomashevskiy [aut], James Craig [aut, cre], Shuhua Hu [ctb], Certara USA, Inc. [cph, fnd]
Maintainer: James Craig <james.craig@certara.com>
Repository: CRAN
Date/Publication: 2024-10-15 17:40:02 UTC

Update Model text file from NLME output File

Description

This function updates a model file with parameter estimates obtained from a dmp file (R structure format of output generated by NLME) text file. The updated model file includes the estimated fixed effects, error terms and random effects values.

Usage

UpdateMDLfrom_dmptxt(
  dmpfile = "dmp.txt",
  SharedWorkingDir = getwd(),
  model_file = "test.mdl",
  compile = TRUE,
  output_file = "test.mdx"
)

Arguments

dmpfile

The path to the DMP text file.

SharedWorkingDir

The working directory. Used if dmpfile, model_file, output_file are given without path.

model_file

The name of the model file to be updated (with optional full path).

compile

A logical value indicating whether to compile the updated model file into NLME executable. Default is TRUE, it also overwrites model_file with updated estimates (i.e. making the same as output_file.)

output_file

The name of the new model file with updated estimates.

Details

TDL5 executable from NLME Engine is used. NLME engine location is identified by INSTALLDIR environment variable. The current function will give an error if TDL5 cannot be executed.

Value

The path to the updated model file.

Checks the local host for GCC version in the path

Description

Performs operating system dependent check for availability of GCC.

Usage

checkGCC(OS.type = .Platform$OS.type)

Arguments

OS.type

Character specifying operating system type. Defaults to .Platform$OS.type.

Value

TRUE if GCC check is successful, otherwise FALSE.

Examples

  checkGCC()

Checks the given directory for the files required for NLME run

Description

Checks the given directory for the files required for NLME run

Usage

checkInstallDir(installDir)

Arguments

installDir

directory Location of NLME executables as set in INSTALLDIR environment variable.

Value

TRUE if all checks are successful, otherwise FALSE.

Examples

## Not run: 
checkInstallDir(Sys.getenv("INSTALLDIR"))

## End(Not run)

Checks if NLME run is licensed

Description

Checks if valid license is available for NLME run.

Usage

checkLicenseFile(installDir, verbose = FALSE, outputGenericInfo = TRUE)

Arguments

installDir

Directory with NLME executables as specified in 'INSTALLDIR' environment variable.

verbose

Flag to output all messages during authorization and licensing. Default is 'FALSE'.

outputGenericInfo

Flag to provide TDL5 output when no issues found. Default is 'TRUE'.

Value

'TRUE' if all checks are successful, otherwise 'FALSE'.

Examples

## Not run: 
checkLicenseFile(Sys.getenv("INSTALLDIR"),
                 verbose = TRUE)

## End(Not run)

Check MPI settings for the given local host

Description

Checks if MPI settings are provided and feasible. Check is done for the hosts where MPI parallel method is used.

Usage

checkMPISettings(obj)

Arguments

obj

NLME Parallel Host to be checked

Value

TRUE if MPI executables are ready for running, otherwise FALSE. If host does not have MPI in parallel method, it also returns TRUE.

Examples

## Not run: 
checkMPISettings(host)

## End(Not run)

Check NLME ROOT DIRECTORY for the given local host

Description

Checks if NLME ROOT DIRECTORY is provided and ready for writing. That directory is used for temporary folders writing.

Usage

checkRootDir(obj)

Arguments

obj

NLME Parallel Host to be checked

Value

TRUE if NLME ROOT DIRECTORY exists and accessible for writing, otherwise FALSE.

Examples

## Not run: 
checkRootDir(host)

## End(Not run)

Table names from the column definition file

Description

Extracts table names from the column definition file

Usage

getTableNames(columnDefinitionFilename, columnDefinitionText, simtbl = FALSE)

Arguments

columnDefinitionFilename

path to NLME column definition file to be read

columnDefinitionText

Lines of column definition file to be used (only if columnDefinitionFilename is not given or NULL).

simtbl

logical. TRUE extracts simulation tables, FALSE extracts simple tables.

Value

vector of names of the tables in column definition file if any, empty string otherwise

Examples

## Not run: 
  getTableNames(columnDefinitionFilename = "cols1.txt",
                simtbl = TRUE)

## End(Not run)

NLME Bootstrap Function

Description

Runs an NLME bootstrap job in parallel and produces summaries

Usage

performBootstrap(args, allowIntermediateResults = TRUE, reportProgress = FALSE)

Arguments

args

Arguments for bootstrap execution

allowIntermediateResults

Set to TRUE to return intermediate results

reportProgress

Set to TRUE to report progress

Value

Directory path where NLME job was executed

Sort specification for multiple estimations

Description

Runs multiple estimations sorting the input dataset by requested columns and creating multiple data sets

Usage

performEstimationOnSortColumns(args, reportProgress = FALSE)

Arguments

args

a vector of arguments provided as the following: c(method, install_directory, shared_directory, localWorkingDir, nlmeArgsFile, numColumns, ColumnNames, NumProc, workflowName)

reportProgress

whether it is required to report the progress (for local jobs usually)

Value

Directory path where NLME job was executed

Runs a set of NLME jobs in parallel

Description

Runs a set of NLME jobs in parallel

Usage

performParallelNLMERun(
  args,
  partialJob = FALSE,
  allowIntermediateResults = TRUE,
  progressStage = "",
  func = "",
  func_arg = NULL,
  reportProgress = FALSE
)

Arguments

args

a vector of arguments provided as the following: c(jobType, parallelMethod, install_dir, shared_directory, localWorkingDir, controlFile, NumProc, workflow_name, fixefUnits)

partialJob

is TRUE if it is not required to stop the job as for covariate stepwise search

allowIntermediateResults

is TRUE if intermediate results are possible like for sorting

progressStage

stage of analysis to be reported

func

function to be executed after NLME job

func_arg

arguments to be provided to the function by name provided above

reportProgress

whether it is required to report the progress (for local jobs usually)

Value

Directory path where NLME job was executed

NLME a profile estimation run on list of fixed effects

Description

This function runs multiple estimations sorting the input dataset by requested columns and creating multiple data sets Runs are also generated for all profiling variables

Usage

performProfileEstimation(args, reportProgress = FALSE)

Arguments

args

Arguments for profile estimation

reportProgress

Set to TRUE to report progress

Value

Directory path where NLME job was executed

Shotgun covariate search

Description

Runs a set of possible covariate sets in parallel

Usage

performShotgunCovarSearch(args, reportProgress = FALSE)

Arguments

args

a vector of arguments provided as the following: c(jobType, parallelMethod, install_dir, shared_directory, localWorkingDir, controlFile, NumProc, workflow_name, fixefUnits)

reportProgress

whether it is required to report the progress (for local jobs usually)

Value

Directory path where NLME job was executed

NLME stepwise covariate search

Description

This function runs a stepwise covariate NLME job in parallel It is designated to be called in commandline (Rscript)

Usage

performStepwiseCovarSearch(args, reportProgress = FALSE)

Arguments

args

a vector of arguments provided as the following: c(method, install_directory, shared_directory, localWorkingDir, modelFile, nlmeArgsFile, listOfFilesToCopy, numCovariates, CovariateNames, NCriteria, addPValue, removePValue, NumProc, workflowName)

reportProgress

whether it is required to report the progress (for local jobs usually)

Value

Directory path where NLME job was executed

Use to reconnect to a grid job

Description

Use to reconnect to a grid job

Usage

reconnectToBootstrapNLMERun(args)

Arguments

args

Arguments for reconnecting to bootstrap grid run

Value

Directory path where NLME job was executed