plotpd {npde}R Documentation

Plots graphs of the normalised prediction distribution errors

Description

Plots 4 graphs to evaluate the shape of the distribution of prediction discrepancies

Usage

plotpd(xobs, pd, ypred)

Arguments

xobs the vector of the observed independent variable (X)
pd the vector of normalised prediction distribution errors (returned by the functions npde or autonpde with the option output=TRUE)
ypred a vector giving the mean of the predicted distribution for each observation

Details

Four graphs are produced: \itema quantile-quantile plotplot of the pd versus the corresponding quantiles of a uniform distribution, with the line y=x overlayed. \itema histogram of the pdthe line corresponding to the uniform distribution is also shown \itemtwo scatterplots of the pda plot of the pd versus the independent variable X and a plot of the pd versus the empirical mean of the predicted distribution; for these last two graphs, we plot the lines corresponding to y=0.5, y=0.05 and y=0.95.

Value

None

Author(s)

Emmanuelle Comets <emmanuelle.comets@bichat.inserm.fr>

References

K. Brendel, E. Comets, C. Laffont, C. Laveille, and F. MentrĂ©. Metrics for external model evaluation with an application to the population pharmacokinetics of gliclazide. Pharmaceutical Research, 23:2036–49, 2006.

See Also

npde, autonpde

Examples


#Computing pd
data(theopp)
data(simtheopp)

x<-autonpde(theopp,simtheopp,1,3,4,boolsave=FALSE,calc.pd=TRUE,calc.npde=FALSE)
x$pd

#Using the npde in object x for the plot
plotpd(x$obsdat$xobs,x$pd,x$ypred)

[Package npde version 1.2 Index]