Hi Fanny, Marc
I was thinking in the same direction as Marc. If you use MCMC (BAYES method in
NONMEM) the algorithm will provide you with samples from the posterior density
(posterior = likelihood * prior). From these samples you can then investigate
different statistics, for example variance
Dear NMusers,
Based on the NONMEM Inter-Occasion Variability (IOV) example control
stream, located at NONMEM_install_dir/examples/example7.ctl, it seems that
it is currently not possible to Mu parameterize IOV in NONMEM 7.3. The
relevant lines from example7.ctl control stream are copypasted
Dear All,
Mango are running a two day R for Pharmacometrics training course to coincide
with this year's PAGE conference in Budapest, Hungary.
This will be satellite training course provided on 5-6 June 2017 at the
Novotel Budapest City hotel.
The R for PK course is designed to review the basic
Thank you all for your responses. It is going to be very useful for my
work.
Best regards,
F.G.
2017-02-15 17:35 GMT+01:00 Williams, Jason :
> Dear Fanny,
>
>
>
> Another useful tool you may want to try is using the mrgsolve package
> available in R, developed by
Dear Fanny,
One additional method to obtain the parameter uncertainty, which I don't
believe was mentioned, is Bayesian estimation using Markov-Chain Monte
Carlo (MCMC) simulation. This method provides a full joint posterior
distribution (e.g. uncertainty distribution) of the parameters and any