dist.pred.sim: Compute distribution of pd/npde using simulations

In npde: Normalised Prediction Distribution Errors for Nonlinear Mixed-Effect Models

Compute distribution of pd/npde using simulations

Description

This function is used to build the distribution of pd/npde using the simulations under the model. The default is to build only the distribution of pd, and to sample from N(0,1) when building the distribution of npde under the null hypothesis.

Usage

dist.pred.sim(npdeObject,nsamp, ...)

Arguments

npdeObject	an object returned by a call to npde or autonpde
nsamp	number of datasets (defaults to 100 or to the number of replications if it is smaller)
...	additional arguments. Currently only the value of calc.npd and calc.npde may be passed on, and will override their corresponding value in the "options" slot of npdeObject

Value

an object of class NpdeObject; the ["results"] slot will contain pd and/or npde for a sample of the simulated datasets (depending on whether calc.npd/calc.npde are set), stored in pd.sim and/or npde.sim

Author(s)

Emmanuelle Comets <[e-mail]>

References

K. Brendel, E. Comets, C. Laffont, C. Laveille, and F. Mentre. 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

data(theopp)
data(simtheopp)
x<-autonpde(theopp,simtheopp,1,3,4,boolsave=FALSE)
# Use random samples from N(0,1) to obtain a prediction interval on the empirical cdf of the npde
plot(x,plot.type="ecdf",bands=TRUE,approx.pi=TRUE)
# defaults to computing the pd and npde for 100 simulated datasets
# (in the theophylline example, this uses all the simulated datasets)
x<-dist.pred.sim(x)
# Use the npde from the simulated datasets to obtain a prediction interval on the empirical cdf
plot(x,plot.type="ecdf",bands=TRUE,approx.pi=FALSE)

npde documentation built on May 29, 2024, 9:59 a.m.