PSM
Population Stochastic Modelling
The PSM package for R provides functions for estimation of linear and
non-linear mixed-effects 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
non-linear time-variant model to be specified, and it also handels
multidimentional input, covariates, missing observations and specification
of dosage regimen.
- Mixed-effects model using stochastic differential equations
- Linear and non-linear models
- Multivariate response
- Multivatiate input
- Missing observations
- Covariates
- Dosage regimen for PK/PD modelling
- Parameter estimation in mixed-effects 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. log-normal 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.
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