create_joint_distribution function

create_joint_distribution

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%.

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

Returns

(Model) Pharmpy model object

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)

See Also

split_joint_distribution : split etas into separate distributions