tQ_model: Model for the tQ Enzyme Kinetics Model

In maomlab/BayesPharma: Tools for Bayesian Analysis of Non-Linear Pharmacology Models

Model for the tQ Enzyme Kinetics Model

Description

Model for the tQ Enzyme Kinetics Model

Usage

tQ_model(
  data,
  formula = tQ_formula(),
  prior = tQ_prior(),
  init = tQ_init(),
  iter = 8000,
  control = list(adapt_delta = 0.99),
  stanvar_function = c(BayesPharma::tQ_stanvar(), BayesPharma::tQ_genquant()),
  expose_functions = TRUE,
  ...
)

Arguments

data	data.frame of experimental data. must contain columns time and P and any predictors specified in the formula.
formula	brms::brmsformula object. To create a dose-response brms::brmsformula, use the tQ_formula function.
prior	brms::brmsprior for kcat, and kM. Use tQ_formula() to create priors to use here.
init	list of lists, numeric value, or "random" for the initial values of the parameters being modeled.
iter	numeric of iterations the model runs. Increasing iter can help with model convergence.
control	a named list of parameters to control the sampler's behavior. Adding max_treedepth and giving a greater value than 10 can improve model convergence.
stanvar_function	stan code for the model
expose_functions	logical. Expose the BayesPharma functions for the model
...	additional arguments passed to brms::brm().

Value

bpfit object, which is a wrapper around a brms::brmsfit object.

References

Choi, B., Rempala, G.A. & Kim, J.K. Beyond the Michaelis-Menten equation: Accurate and efficient estimation of enzyme kinetic parameters. Sci Rep 7, 17018 (2017). https://doi.org/10.1038/s41598-017-17072-z

See Also

tQ_formula, tQ_prior, tQ_init, or tQ_stanvar

maomlab/BayesPharma documentation built on Aug. 24, 2024, 8:45 a.m.