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PFIM (version 7.0.2)

Population Fisher Information Matrix

Description

Evaluate or optimize designs for nonlinear mixed effects models using the Fisher Information matrix. Methods used in the package refer to Mentré F, Mallet A, Baccar D (1997) , Retout S, Comets E, Samson A, Mentré F (2007) , Bazzoli C, Retout S, Mentré F (2009) , Le Nagard H, Chao L, Tenaillon O (2011) , Combes FP, Retout S, Frey N, Mentré F (2013) and Seurat J, Tang Y, Mentré F, Nguyen TT (2021) .

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Version

Install

install.packages('PFIM')

Monthly Downloads

257

Version

7.0.2

License

GPL (>= 3)

Homepage

http://www.pfim.biostat.fr/

Maintainer

Romain Leroux

Last Published

January 30th, 2026

Functions in PFIM (7.0.2)

Linear2BolusSingleDose_ClQV1V2

Model Linear2BolusSingleDose_ClQV1V2

LibraryOfPKModels

LibraryOfPKModels

Linear2FirstOrderSteadyState_kakk12k21Vtau

Model Linear2FirstOrderSteadyState_kakk12k21Vtau

Linear2InfusionSteadyState_kk12k21Vtau

Model Linear2InfusionSteadyState_kk12k21Vtau

Linear2FirstOrderSingleDose_kakk12k21V

Model Linear2FirstOrderSingleDose_kakk12k21V

Linear2FirstOrderSteadyState_kaClQV1V2tau

Model Linear2FirstOrderSteadyState_kaClQV1V2tau

Linear2InfusionSteadyState_ClQV1V2tau

Model Linear2InfusionSteadyState_ClQV1V2tau

Linear2InfusionSingleDose_kk12k21V

Model Linear2InfusionSingleDose_kk12k21V

Linear2InfusionSingleDose_ClQV1V2

Model Linear2InfusionSingleDose_ClQV1V2

ModelAnalyticSteadyState

ModelAnalyticSteadyState

ModelAnalyticInfusionSteadyState

ModelAnalyticInfusionSteadyState

Linear2BolusSteadyState_ClQV1V2tau

Model Linear2BolusSteadyState_ClQV1V2tau

ModelODEDoseInEquations

ModelODEDoseNotInEquations

ModelAnalyticInfusion

ModelAnalyticInfusion

Linear2BolusSingleDose_kk12k21V

Model Linear2BolusSingleDose_kk12k21V

Linear2FirstOrderSingleDose_kaClQV1V2

Model Linear2FirstOrderSingleDose_kaClQV1V2

Fisher Information matrix for design evaluation/optimization for nonlinear mixed effects models.

Linear2BolusSteadyState_kk12k21Vtau

Model Linear2BolusSteadyState_kk12k21Vtau

ModelODEInfusion

ModelODEInfusion

ModelODEDoseNotInEquations

ModelODEDoseNotInEquations

ModelODEInfusionDoseInEquation

ModelODEInfusionDoseInEquation

SimplexAlgorithm

SimplexAlgorithm

armAdministration

getArmAdministration: get the administration parameters of an arm.

MultiplicativeAlgorithm

MultiplicativeAlgorithm

MultiplicativeAlgorithm_Rcpp

Function MultiplicativeAlgorithm_Rcpp

adjustGradient: adjust the gradient for the log normal distribution.

Generate optimization report

SamplingTimeConstraints

SamplingTimeConstraints

defineModelWrapper

defineModelWrapper: define the model wrapper for the ode solver

defineModelType

defineModelType: define the class of the model to be evaluated.

defineModelAdministration

defineModelAdministration: define the administration

defineModelEquationsFromLibraryOfModel

defineModelEquationsFromLibraryOfModel: define the model equations giving the models in the library of models.

generateReportOptimization

generateReportOptimization: generate the report for the design optimization.

evaluateInitialConditions

evaluateInitialConditions: evaluate the initial conditions.

evaluateFim: evaluation of the Fim

constraintsTableForReport

constraintsTableForReport: table of the PGBOAlgorithm constraints for the report.

convertPKModelAnalyticToPKModelODE

convertPKModelAnalyticToPKModelODE: conversion from analytic to ode

define the type of Fisher information matrix: population, individual or Bayesian

evaluateArm: evaluation of the model with the arm parameters.

definePKPDModel

definePKPDModel: define a PKPD model from library of model

Compute the fun.amoeba

generateDosesCombination

generateDosesCombination: generate the combination for the doses.

defineOptimizationAlgorithm

Define optimization algorithm

generateFimsFromConstraints

Generate FIMs from constraints

definePKModel: define a PK model from library of model

getDeterminant: get the determinant

getDcriterion : get the Dcriterion

generateSamplingTimesCombination

generateSamplingTimesCombination: generate the combination for the samplings.

getModelParametersData

getModelParametersData: get model parameters data for report.

getFim: get the Fisher matrix.

getFisherMatrix

getFisherMatrix: display the Fisher matrix components

plotEvaluation: plots for the evaluation of the model responses.

plotEvaluationResults

plotEvaluationResults: process for the evaluation of the responses.

generateReportEvaluation

generateReportEvaluation: generate the report for the model evaluation.

getShrinkage: get the shrinkage

evaluateDesign: evaluation of a design.

getArmData: extract arm data for The Report

plotShrinkage: plot the shrinkage values.

Compute the fisher.simplex

finiteDifferenceHessian

finiteDifferenceHessian: compute the Hessian

plotFrequencies

Plot frequencies for the FedorovWynn algorithm

generateSamplingsFromSamplingConstraints

generateSamplingsFromSamplingConstraints

getCorrelationMatrix

getCorrelationMatrix : get the correlation matrix

getArmConstraints

getArmConstraints: get the administration and sampling time constraints for the MultiplicativeAlgorithm.

evaluateErrorModelDerivatives

evaluateErrorModelDerivatives; evaluate the derivatives of the model error.

processArmEvaluationResults

processArmEvaluationResults: process for the evaluation of an arm.

plotEvaluationSI

plotEvaluationSI: process for the evaluation of the gradient of the responses.

plotWeightsMultiplicativeAlgorithm

plotWeightsMultiplicativeAlgorithm: plot the optimal weight.

plotRSEFIM: barplot for the RSE

Optimization PGBOAlgorithm

plotFrequenciesFedorovWynnAlgorithm

plotFrequenciesFedorovWynnAlgorithm

getRSE: get the RSE

replaceVariablesLibraryOfModels

replaceVariablesLibraryOfModels: replace variable in the LibraryOfModels

Plot standard errors

processArmEvaluationSI

processArmEvaluationSI: process for the evaluation of the gradient of the responses.

plotSensitivityIndices

Plot sensitivity indices.

plotSEFIM: barplot for the SE

Plot relative standard errors

updateSamplingTimes

updateSamplingTimes: update sampling times for plotting used for plot

tablesForReport

tablesForReport: generate the table for the report.

checkValiditySamplingConstraint

checkValiditySamplingConstraint: check if the constraints used for the design optimization are valid.

evaluateModelVariance

evaluateModelVariance: evaluate the variance of the model

Show optimization results

showFIM: show the Fim in the R console.

getModelErrorData

getModelErrorData: get the parameters sigma slope and sigma inter (used for the report).

setSamplingConstraintForOptimization

setSamplingConstraintForOptimization: set the sampling time constraints for an arm for the design optimization.

Plot weights for the multiplicative algorithm

setOptimalArms: set the optimal arms of an optimization algorithm.

checkSamplingTimeConstraintsForMetaheuristic

checkSamplingTimeConstraintsForMetaheuristic

evaluateModelGradient

evaluateModelGradient: evaluate the gradient of the model

evaluateModel: evaluate the model

getSE: get the SE

evaluateVarianceFIM

evaluateVarianceFIM: evaluate the variance

getListLastName

getListLastName: routine to get the names of last element of a nested list.

getSamplingData

getSamplingData: extract sampling times and max sampling time used for plot.

Run optimization

setEvaluationFim

setEvaluationFim: set the Fim results.

Dcriterion: get the D-criterion of the Fim.

AdministrationConstraints

AdministrationConstraints

LibraryOfModels

LibraryOfModels

LibraryOfPDModels

LibraryOfPDModels

FedorovWynnAlgorithm_Rcpp

Fedorov-Wynn algorithm in Rcpp.

FedorovWynnAlgorithm

FedorovWynnAlgorithm