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R
nlmixr

gen_saem_user_fn

Generate an SAEM model

Description

Generate an SAEM model using either closed-form solutions or ODE-based model definitions

Usage

gen_saem_user_fn(
  model,
  PKpars = attr(model, "default.pars"),
  pred = NULL,
  err = NULL,
  control = saemControl(),
  inPars = NULL
)

Arguments

model

a compiled SAEM model by gen_saem_user_fn()
PKpars

PKpars function
pred

pred function; This will be a focei-style pred
inPars

a character vector of parameters to be read from the input dataset (including time varying covariates)

Details

Fit a generalized nonlinear mixed-effect model using the Stochastic Approximation Expectation-Maximization (SAEM) algorithm

Value

A user function based on the model to run the SAEM code

Author(s)

Matthew Fidler & Wenping Wang

nlmixr

Nonlinear Mixed Effects Models in Population PK/PD

v2.0.4
GPL (>= 2)
Authors
Matthew Fidler [aut] (<https://orcid.org/0000-0001-8538-6691>), Yuan Xiong [aut], Rik Schoemaker [aut] (<https://orcid.org/0000-0002-7538-3005>), Justin Wilkins [aut] (<https://orcid.org/0000-0002-7099-9396>), Wenping Wang [aut, cre], Robert Leary [ctb], Mason McComb [aut] (<https://orcid.org/0000-0001-9871-8616>), Mirjam Trame [ctb], Teun Post [ctb], Richard Hooijmaijers [aut], Hadley Wickham [ctb], Dirk Eddelbuettel [cph], Johannes Pfeifer [ctb], Robert B. Schnabel [ctb], Elizabeth Eskow [ctb], Emmanuelle Comets [ctb], Audrey Lavenu [ctb], Marc Lavielle [ctb], David Ardia [cph], Daniel C. Dillon [ctb], Katharine Mullen [cph], Ben Goodrich [ctb]
Initial release

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