Generate an SAEM model using either closed-form solutions or ODE-based model definitions
gen_saem_user_fn(
model,
PKpars = attr(model, "default.pars"),
pred = NULL,
err = NULL,
control = saemControl(),
inPars = NULL
)a compiled SAEM model by gen_saem_user_fn()
PKpars function
pred function; This will be a focei-style pred
a character vector of parameters to be read from the input dataset (including time varying covariates)
A user function based on the model to run the SAEM code
Fit a generalized nonlinear mixed-effect model using the Stochastic Approximation Expectation-Maximization (SAEM) algorithm