saem.fit: Fit an SAEM model

saem.fitR Documentation

Fit an SAEM model

Description

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

Usage

saem.fit(
  model,
  data,
  inits,
  PKpars = NULL,
  pred = NULL,
  covars = NULL,
  mcmc = list(niter = c(200, 300), nmc = 3, nu = c(2, 2, 2)),
  ODEopt = list(atol = 1e-06, rtol = 1e-04, method = "lsoda", transitAbs = FALSE),
  distribution = c("normal", "poisson", "binomial", "lnorm"),
  seed = 99
)

saem(
  model,
  data,
  inits,
  PKpars = NULL,
  pred = NULL,
  covars = NULL,
  mcmc = list(niter = c(200, 300), nmc = 3, nu = c(2, 2, 2)),
  ODEopt = list(atol = 1e-06, rtol = 1e-04, method = "lsoda", transitAbs = FALSE),
  distribution = c("normal", "poisson", "binomial", "lnorm"),
  seed = 99
)

## S3 method for class 'fit.nlmixr.ui.nlme'
saem(
  model,
  data,
  inits,
  PKpars = NULL,
  pred = NULL,
  covars = NULL,
  mcmc = list(niter = c(200, 300), nmc = 3, nu = c(2, 2, 2)),
  ODEopt = list(atol = 1e-06, rtol = 1e-04, method = "lsoda", transitAbs = FALSE),
  distribution = c("normal", "poisson", "binomial", "lnorm"),
  seed = 99
)

## S3 method for class 'fit.function'
saem(
  model,
  data,
  inits,
  PKpars = NULL,
  pred = NULL,
  covars = NULL,
  mcmc = list(niter = c(200, 300), nmc = 3, nu = c(2, 2, 2)),
  ODEopt = list(atol = 1e-06, rtol = 1e-04, method = "lsoda", transitAbs = FALSE),
  distribution = c("normal", "poisson", "binomial", "lnorm"),
  seed = 99
)

## S3 method for class 'fit.nlmixrUI'
saem(
  model,
  data,
  inits,
  PKpars = NULL,
  pred = NULL,
  covars = NULL,
  mcmc = list(niter = c(200, 300), nmc = 3, nu = c(2, 2, 2)),
  ODEopt = list(atol = 1e-06, rtol = 1e-04, method = "lsoda", transitAbs = FALSE),
  distribution = c("normal", "poisson", "binomial", "lnorm"),
  seed = 99
)

## S3 method for class 'fit.RxODE'
saem(
  model,
  data,
  inits,
  PKpars = NULL,
  pred = NULL,
  covars = NULL,
  mcmc = list(niter = c(200, 300), nmc = 3, nu = c(2, 2, 2)),
  ODEopt = list(atol = 1e-06, rtol = 1e-04, method = "lsoda", transitAbs = FALSE),
  distribution = c("normal", "poisson", "binomial", "lnorm"),
  seed = 99
)

## S3 method for class 'fit.default'
saem(
  model,
  data,
  inits,
  PKpars = NULL,
  pred = NULL,
  covars = NULL,
  mcmc = list(niter = c(200, 300), nmc = 3, nu = c(2, 2, 2)),
  ODEopt = list(atol = 1e-06, rtol = 1e-04, method = "lsoda", transitAbs = FALSE),
  distribution = c("normal", "poisson", "binomial", "lnorm"),
  seed = 99
)

Arguments

model

an RxODE model or lincmt()

data

input data

inits

initial values

PKpars

PKpars function

pred

pred function

covars

Covariates in data

mcmc

a list of various mcmc options

ODEopt

optional ODE solving options

distribution

one of c("normal","poisson","binomial")

seed

seed for random number generator

Details

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

Value

saem fit object

Author(s)

Matthew Fidler & Wenping Wang


nlmixr documentation built on March 27, 2022, 5:05 p.m.

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