Population Fisher Information Matrix


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Documentation for package ‘PFIM’ version 7.0

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A B C D E F G I L M N O P R S T U

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

-- A --

adjustGradient adjustGradient: adjust the gradient for the log normal distribution.
Administration Administration
AdministrationConstraints AdministrationConstraints
Arm Arm
armAdministration getArmAdministration: get the administration parameters of an arm.

-- B --

BayesianFim BayesianFim

-- C --

checkSamplingTimeConstraintsForMetaheuristic checkSamplingTimeConstraintsForMetaheuristic
checkValiditySamplingConstraint checkValiditySamplingConstraint: check if the constraints used for the design optimization are valid.
Combined1 Combined1
computeVMat computeVMat
Constant Constant
constraintsTableForReport constraintsTableForReport: table of the PGBOAlgorithm constraints for the report.
convertPKModelAnalyticToPKModelODE convertPKModelAnalyticToPKModelODE: conversion from analytic to ode

-- D --

Dcriterion Dcriterion: get the D-criterion of the Fim.
defineFim define the type of Fisher information matrix: population, individual or Bayesian
defineModelAdministration defineModelAdministration: define the administration
defineModelEquationsFromLibraryOfModel defineModelEquationsFromLibraryOfModel: define the model equations giving the models in the library of models.
defineModelType defineModelType: define the class of the model to be evaluated.
defineModelWrapper defineModelWrapper: define the model wrapper for the ode solver
defineOptimizationAlgorithm Define optimization algorithm
definePKModel definePKModel: define a PK model from library of model
definePKPDModel definePKPDModel: define a PKPD model from library of model
Design Design
Distribution Distribution

-- E --

evaluateArm evaluateArm: evaluation of the model with the arm parameters.
evaluateDesign evaluateDesign: evaluation of a design.
evaluateErrorModelDerivatives evaluateErrorModelDerivatives; evaluate the derivatives of the model error.
evaluateFim evaluateFim: evaluation of the Fim
evaluateInitialConditions evaluateInitialConditions: evaluate the initial conditions.
evaluateModel evaluateModel: evaluate the model
evaluateModelGradient evaluateModelGradient: evaluate the gradient of the model
evaluateModelVariance evaluateModelVariance: evaluate the variance of the model
evaluateVarianceFIM evaluateVarianceFIM: evaluate the variance
Evaluation Evaluation

-- F --

FedorovWynnAlgorithm FedorovWynnAlgorithm
FedorovWynnAlgorithm_Rcpp Fedorov-Wynn algorithm in Rcpp.
Fim Fim
finiteDifferenceHessian finiteDifferenceHessian: compute the Hessian
fisherSimplex Compute the fisher.simplex
fun.amoeba Compute the fun.amoeba

-- G --

generateDosesCombination generateDosesCombination: generate the combination for the doses.
generateFimsFromConstraints Generate FIMs from constraints
generateReportEvaluation generateReportEvaluation: generate the report for the model evaluation.
generateReportOptimization generateReportOptimization: generate the report for the design optimization.
generateSamplingsFromSamplingConstraints generateSamplingsFromSamplingConstraints
generateSamplingTimesCombination generateSamplingTimesCombination: generate the combination for the samplings.
getArmConstraints getArmConstraints: get the administration and sampling time constraints for the MultiplicativeAlgorithm.
getArmData getArmData: extract arm data for The Report
getCorrelationMatrix getCorrelationMatrix : get the correlation matrix
getDcriterion getDcriterion : get the Dcriterion
getDeterminant getDeterminant: get the determinant
getFim getFim: get the Fisher matrix.
getFisherMatrix getFisherMatrix: display the Fisher matrix components
getListLastName getListLastName: routine to get the names of last element of a nested list.
getModelErrorData getModelErrorData: get the parameters sigma slope and sigma inter (used for the report).
getModelParametersData getModelParametersData: get model parameters data for report.
getRSE getRSE: get the RSE
getSamplingData getSamplingData: extract sampling times and max sampling time used for plot.
getSE getSE: get the SE
getShrinkage getShrinkage: get the shrinkage

-- I --

IndividualFim IndividualFim

-- L --

LibraryOfModels LibraryOfModels
LibraryOfPDModels LibraryOfPDModels
LibraryOfPKModels LibraryOfPKModels
Linear2BolusSingleDose_ClQV1V2 Model Linear2BolusSingleDose_ClQV1V2
Linear2BolusSingleDose_kk12k21V Model Linear2BolusSingleDose_kk12k21V
Linear2BolusSteadyState_ClQV1V2tau Model Linear2BolusSteadyState_ClQV1V2tau
Linear2BolusSteadyState_kk12k21Vtau Model Linear2BolusSteadyState_kk12k21Vtau
Linear2FirstOrderSingleDose_kaClQV1V2 Model Linear2FirstOrderSingleDose_kaClQV1V2
Linear2FirstOrderSingleDose_kakk12k21V Model Linear2FirstOrderSingleDose_kakk12k21V
Linear2FirstOrderSteadyState_kaClQV1V2tau Model Linear2FirstOrderSteadyState_kaClQV1V2tau
Linear2FirstOrderSteadyState_kakk12k21Vtau Model Linear2FirstOrderSteadyState_kakk12k21Vtau
Linear2InfusionSingleDose_ClQV1V2 Model Linear2InfusionSingleDose_ClQV1V2
Linear2InfusionSingleDose_kk12k21V Model Linear2InfusionSingleDose_kk12k21V
Linear2InfusionSteadyState_ClQV1V2tau Model Linear2InfusionSteadyState_ClQV1V2tau
Linear2InfusionSteadyState_kk12k21Vtau Model Linear2InfusionSteadyState_kk12k21Vtau
LogNormal LogNormal

-- M --

Model Model
ModelAnalytic ModelAnalytic
ModelAnalyticInfusion ModelAnalyticInfusion
ModelAnalyticInfusionSteadyState ModelAnalyticInfusionSteadyState
ModelAnalyticSteadyState ModelAnalyticSteadyState
ModelError ModelError
ModelInfusion ModelInfusion
ModelODE ModelODE
ModelODEBolus ModelODEBolus
ModelODEDoseInEquations ModelODEDoseNotInEquations
ModelODEDoseNotInEquations ModelODEDoseNotInEquations
ModelODEInfusion ModelODEInfusion
ModelODEInfusionDoseInEquation ModelODEInfusionDoseInEquation
ModelParameter ModelParameter
MultiplicativeAlgorithm MultiplicativeAlgorithm
MultiplicativeAlgorithm_Rcpp Function MultiplicativeAlgorithm_Rcpp

-- N --

Normal Normal

-- O --

Optimization Optimization
optimizeDesign Optimization PGBOAlgorithm

-- P --

package-PFIM Fisher Information matrix for design evaluation/optimization for nonlinear mixed effects models.
PFIM Fisher Information matrix for design evaluation/optimization for nonlinear mixed effects models.
PFIM, Fisher Information matrix for design evaluation/optimization for nonlinear mixed effects models.
PFIMProject PFIMProject
PGBOAlgorithm PGBOAlgorithm
plotEvaluation plotEvaluation: plots for the evaluation of the model responses.
plotEvaluationResults plotEvaluationResults: process for the evaluation of the responses.
plotEvaluationSI plotEvaluationSI: process for the evaluation of the gradient of the responses.
plotFrequencies Plot frequencies for the FedorovWynn algorithm
plotFrequenciesFedorovWynnAlgorithm plotFrequenciesFedorovWynnAlgorithm
plotRSE Plot relative standard errors
plotRSEFIM plotRSEFIM: barplot for the RSE
plotSE Plot standard errors
plotSEFIM plotSEFIM: barplot for the SE
plotSensitivityIndices Plot sensitivity indices.
plotShrinkage plotShrinkage: plot the shrinkage values.
plotWeights Plot weights for the multiplicative algorithm
plotWeightsMultiplicativeAlgorithm plotWeightsMultiplicativeAlgorithm: plot the optimal weight.
PopulationFim PopulationFim
processArmEvaluationResults processArmEvaluationResults: process for the evaluation of an arm.
processArmEvaluationSI processArmEvaluationSI: process for the evaluation of the gradient of the responses.
Proportional Proportional
PSOAlgorithm PSOAlgorithm

-- R --

replaceVariablesLibraryOfModels replaceVariablesLibraryOfModels: replace variable in the LibraryOfModels
Report Generate optimization report
run Run optimization

-- S --

SamplingTimeConstraints SamplingTimeConstraints
SamplingTimes SamplingTimes
setEvaluationFim setEvaluationFim: set the Fim results.
setOptimalArms setOptimalArms: set the optimal arms of an optimization algorithm.
setSamplingConstraintForOptimization setSamplingConstraintForOptimization: set the sampling time constraints for an arm for the design optimization.
show Show optimization results
showFIM showFIM: show the Fim in the R console.
SimplexAlgorithm SimplexAlgorithm

-- T --

tablesForReport tablesForReport: generate the table for the report.

-- U --

updateSamplingTimes updateSamplingTimes: update sampling times for plotting used for plot