testnpde {npde} | R Documentation |
Performs tests for the normalised prediction distribution errors returned by
npde
testnpde(npde)
npde |
the vector of prediction distribution errors (returned by the
functions npde or autonpde with the option output=TRUE) |
Given a vector of normalised prediction distribution errors (npde) computed by npde
or autonpde
, this function compares the npde to the standardised
normal distribution N(0,1) using a Wilcoxon test of the mean, a Fisher test of the
variance, and a Shapiro-Wilks test for normality. A global test is also
reported.
a list containing 4 components:
Wilcoxon test of mean=0 |
compares the mean of the npde to 0 using a Wilcoxon test |
variance test |
compares the variance of the npde to 1 using a Fisher test |
SW test of normality |
compares the npde to the normal distribution using a Shapiro-Wilks test |
global test |
an adjusted p-value corresponding to the minimum of the 3 previous p-values multiplied by the number of tests (3), or 1 if this p-value is larger than 1. |
Emmanuelle Comets <emmanuelle.comets@bichat.inserm.fr>
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.
#Computing npde data(theopp) data(simtheopp) x<-autonpde(theopp,simtheopp,1,3,4,boolsave=FALSE) #Testing npde y<-testnpde(x$npde) # Not Run # Assuming the results were saved to a file output.npde # using the boolsave=T option and namsav="output" (default) # dat<-read.table("output.npde",header=T) # testnpde(dat$npde)