create_joint_distribution {pharmr} | R Documentation |
create_joint_distribution
Description
Combines some or all etas into a joint distribution.
The etas must be IIVs and cannot be fixed. Initial estimates for covariance between the etas is dependent on whether the model has results from a previous run. In that case, the correlation will be calculated from individual estimates, otherwise correlation will be set to 10%.
Usage
create_joint_distribution(model, rvs = NULL, individual_estimates = NULL)
Arguments
model |
(Model) Pharmpy model |
rvs |
(array(str) (optional)) Sequence of etas or names of etas to combine. If NULL, all etas that are IIVs and non-fixed will be used (full block). NULL is default. |
individual_estimates |
(data.frame (optional)) Optional individual estimates to use for calculation of initial estimates |
Value
(Model) Pharmpy model object
See Also
split_joint_distribution : split etas into separate distributions
Examples
## Not run:
model <- load_example_model("pheno")
model$random_variables$etas
model <- create_joint_distribution(model, c('ETA_CL', 'ETA_VC'))
model$random_variables$etas
## End(Not run)
[Package pharmr version 1.0.1 Index]