default.saemix.plots: Wrapper functions to produce certain sets of default plots

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/func_plots.R

Description

These functions produce default sets of plots, corresponding to diagnostic or individual fits.

Usage

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default.saemix.plots(saemixObject, ...)

Arguments

saemixObject

an object returned by the saemix function

...

optional arguments passed to the plots

Details

These functions are wrapper functions designed to produce default sets of plots to help the user assess their model fits.

Value

Depending on the type argument, the following plots are produced:

Author(s)

Emmanuelle Comets <emmanuelle.comets@inserm.fr>, Audrey Lavenu, Marc Lavielle.

References

Comets E, Lavenu A, Lavielle M. Parameter estimation in nonlinear mixed effect models using saemix, an R implementation of the SAEM algorithm. Journal of Statistical Software 80, 3 (2017), 1-41.

Kuhn E, Lavielle M. Maximum likelihood estimation in nonlinear mixed effects models. Computational Statistics and Data Analysis 49, 4 (2005), 1020-1038.

Comets E, Lavenu A, Lavielle M. SAEMIX, an R version of the SAEM algorithm. 20th meeting of the Population Approach Group in Europe, Athens, Greece (2011), Abstr 2173.

See Also

saemix, saemix.plot.data, saemix.plot.setoptions, plot.saemix

Examples

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data(theo.saemix)

saemix.data<-saemixData(name.data=theo.saemix,header=TRUE,sep=" ",na=NA, 
  name.group=c("Id"),name.predictors=c("Dose","Time"),
  name.response=c("Concentration"),name.covariates=c("Weight","Sex"),
  units=list(x="hr",y="mg/L",covariates=c("kg","-")), name.X="Time")

model1cpt<-function(psi,id,xidep) { 
	  dose<-xidep[,1]
	  tim<-xidep[,2]  
	  ka<-psi[id,1]
	  V<-psi[id,2]
	  CL<-psi[id,3]
	  k<-CL/V
	  ypred<-dose*ka/(V*(ka-k))*(exp(-k*tim)-exp(-ka*tim))
	  return(ypred)
}

saemix.model<-saemixModel(model=model1cpt,
  description="One-compartment model with first-order absorption", 
  psi0=matrix(c(1.,20,0.5,0.1,0,-0.01),ncol=3, byrow=TRUE,
  dimnames=list(NULL, c("ka","V","CL"))),transform.par=c(1,1,1),
  covariate.model=matrix(c(0,1,0,0,0,0),ncol=3,byrow=TRUE),fixed.estim=c(1,1,1),
  covariance.model=matrix(c(1,0,0,0,1,0,0,0,1),ncol=3,byrow=TRUE),
  omega.init=matrix(c(1,0,0,0,1,0,0,0,1),ncol=3,byrow=TRUE),error.model="constant")

# Reducing the number of iterations due to time constraints for CRAN
saemix.options<-list(seed=632545,save=FALSE,save.graphs=FALSE,nbiter.saemix=c(100,100))

saemix.fit<-saemix(saemix.model,saemix.data,saemix.options)

default.saemix.plots(saemix.fit)

# Not run (time constraints for CRAN)
# basic.gof(saemix.fit)

# Not run (time constraints for CRAN)
# advanced.gof(saemix.fit)

individual.fits(saemix.fit)

saemixr/saemix documentation built on Jan. 26, 2020, 12:53 a.m.