-
Notifications
You must be signed in to change notification settings - Fork 28
Priors in the d2d framework
tmaiwald edited this page May 19, 2015
·
8 revisions
Prior knowledge about parameters can be considered as well. If knowledge is available, a Gaussian distribution can be used as a penalisation term for individual parameters by setting
#!matlab
ar.type(jp)=1;
for a normal distributed penalisation term,
#!matlab
ar.type(jp)=2;
for a uniform distributed penalisation term with normal bounds and
#!matlab
ar.type(jp)=3;
for a L1 penalisation term.
To specify
- Installation and system requirements
- Setting up models
- First steps
- Advanced events and pre-equilibration
- Computation of integration-based prediction bands
- How is the architecture of the code and the most important commands?
- What are the most important fields of the global variable ar?
- What are the most important functions?
- Optimization algorithms available in the d2d-framework
- Objective function, likelhood and chi-square in the d2d framework
- How to set up priors?
- How to set up steady state constraints?
- How do I restart the solver upon a step input?
- How to deal with integrator tolerances?
- How to implement a bolus injection?
- How to implement washing and an injection?
- How to implement a moment ODE model?
- How to run PLE calculations on a Cluster?