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In PFIM: Population Fisher Information Matrix

library(knitr)
library(kableExtra)
options(kableExtra.latex.load_packages = FALSE)
options(kableExtra.auto_format = FALSE)
knitr::opts_chunk$set(echo = TRUE)

title_shrinkage = FALSE
plotWeight = FALSE
variance_components = TRUE
output = knitrFIM(object)
if ( output$typeOfFIM[1] == "BayesianFim" ){
  title_shrinkage = TRUE
  variance_components = FALSE
}
if ( output$typeOfFIM[1] == "PopulationFim" ){
  plotWeight = TRUE
}

Model equations

knitrModelEquations( object )

Error model

knitrModelError(object)

Model parameters

knitrModelParameters( object )

Administration parameters

knitrAdministrationParameters( object )

Initial design

knitrInitialDesigns( object )

Determinant, condition numbers and D-criteria of the FIM

output = knitrFIM( object )
output$criteriaFimInitialDesign

Optimal design

knitrOptimalDesign( object )

Fisher information matrix

Fixed effects

output = knitrFIM( object )
output$fIMFixedEffects 

r if ( variance_components ) '### Variance components'

output = knitrFIM( object )
output$fIMRandomEffects

Correlation matrix

Fixed effects

output = knitrFIM( object )
output$correlationFixedEffects 

r if ( variance_components ) '### Variance components'

output = knitrFIM( object )
output$correlationRandomEffects 

Determinant, condition numbers and D-criteria of the FIM

output = knitrFIM( object )
output$criteriaFim

r if ( title_shrinkage ) '## Values for SE and RSE and shrinkage'

output = knitrFIM( object )
output$se_rse

r if ( variance_components ) '## Values for SE and RSE '

output = knitrFIM( object )
output$se_rse

Graphs of the responses

for (i in 1:length(plotResponses))
{
print(plotResponses[[i]])
}

Graphs of the SE and RSE

SE =plotSE( object )
print(SE[[1]])
RSE = plotRSE( object )
print(RSE[[1]])

r if ( title_shrinkage ) '# Graph of shrinkage'

if ( title_shrinkage ==TRUE){
shrinkage = plotShrinkage( object )
print(shrinkage[[1]])}

r if ( plotWeight ) '# Graph for the optimal weights'

output = plotWeightOptimisation( object, weightThreshold )
for ( i in 1:length( output$plot[[1]] ) )
{
print(output$plot[[1]][[i]] )
}

PFIM documentation built on June 24, 2022, 9:06 a.m.