Dear Fanny,
I would use either bootstrapping or likelihood profiling, both of them are
implemented in PsN ('bootstrap' and 'llp').
Kind regards
Max Taubert
________________________________
Von: [email protected] [[email protected]]" im Auftrag
von "Fanny Gallais [[email protected]]
Gesendet: Mittwoch, 15. Februar 2017 11:55
An: [email protected]
Betreff: [NMusers] Parameter uncertainty
Dear NM users,
I would like to perform a simulation (on R) incorporating parameter
uncertainty. For now I'm working on a simple PK model. Parameters were
estimated with NONMEM. I'm trying to figure out what is the best way to assess
parameter uncertainty. I've read about using the standard errors reported by
NONMEM and assume a normal distribution. The main problem is this can lead to
negative values. Another approach would be a more computational non-parametric
method like bootstrap. Do you know other methods to assess parameter
uncertainty?
Best regards
F. Gallais
