calcnpde {npde} | R Documentation |
For each subject, this function computes the prediction errors and returns the decorrelated simulated and observed data.
calcnpde(isuj, msuj, matsim, nrep, verbose)
isuj |
subject ID |
msuj |
observed data for the subject, a dataframe containing 3 columns (id=patient ID, xobs=independent variable (X), yobs=dependent variable (Y) |
matsim |
simulated data for the subject, a dataframe containing 4 columns (idsim=patient ID, irsim=integer identifying the replicate; xsim=independent variable (X), ysim=dependent variable (Y) |
nrep |
number of replications |
verbose |
a boolean (T if messages are to be printed as each subject is processed, F otherwise) |
xerr |
an integer code to keep track of errors during the computation;
after a successful computation the value of xerr should be 0. A value
of 1 or 2 signals errors during the computation. |
pde |
the vector of prediction distribution errors for the subject |
ydsim |
the vector of simulated dependent variable (Y) for the subject, decorrelated |
ydobs |
the vector of observed dependent variable (Y) for the subject, decorrelated |
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.