PSM
Population Stochastic Modelling
The PSM package for R provides functions for estimation of linear and
nonlinear mixedeffects models using stochastic differential equations.
Moreover it provides functions for finding smoothed estimates of
model states and for simulation. The package allows for any multivariate
nonlinear timevariant model to be specified, and it also handels
multidimentional input, covariates, missing observations and specification
of dosage regimen.
 Mixedeffects model using stochastic differential equations
 Linear and nonlinear models
 Multivariate response
 Multivatiate input
 Missing observations
 Covariates
 Dosage regimen for PK/PD modelling
 Parameter estimation in mixedeffects model using maximum likelihood
(FOCE approximation)
 It is possible to use a simple pooled likelihood function
by using a model without random effects
 Random effects can be normally distributed or any transformation
hereof (e.g. lognormal etc.)
 Simulation of data based on new or estimated model
 Smoothing estimates of model states for optimal use of data
PSM is a package for R
published under the GPL 2 license. The program has been developed
at Informatics and Mathematical Modelling (IMM)
at the Technical University of Denmark (DTU).
PSM builds upon CTSM which
has been develloped mainly for single individual modelling but also
handles multiple individuals using a pooled likehood. CTSM is based
on Fortran and will thus generally run faster than PSM for identical
models.
